Tumor Area Research Articles

Chondrosarcoma evaluation using hematein-based x-ray staining and high-resolution 3D micro-CT: a feasibility study

BackgroundChondrosarcomas are rare malignant bone tumors diagnosed by analyzing radiological images and histology of tissue biopsies and evaluating features such as matrix calcification, cortical destruction, trabecular penetration, and tumor cell entrapment.MethodsWe retrospectively analyzed 16 cartilaginous tumor tissue samples from three patients (51-, 54-, and 70-year-old) diagnosed with a dedifferentiated chondrosarcoma at the femur, a moderately differentiated chondrosarcoma in the pelvis, and a predominantly moderately differentiated chondrosarcoma at the scapula, respectively. We combined a hematein-based x-ray staining with high-resolution three-dimensional (3D) microscopic x-ray computed tomography (micro-CT) for nondestructive 3D tumor assessment and tumor margin evaluation.ResultsWe detected trabecular entrapment on 3D micro-CT images and followed bone destruction throughout the volume. In addition to staining cell nuclei, hematein-based staining also improved the visualization of the tumor matrix, allowing for the distinction between the tumor and the bone marrow cavity. The hematein-based staining did not interfere with further conventional histology. There was a 5.97 ± 7.17% difference between the relative tumor area measured using micro-CT and histopathology (p = 0.806) (Pearson correlation coefficient r = 0.92, p = 0.009). Signal intensity in the tumor matrix (4.85 ± 2.94) was significantly higher in the stained samples compared to the unstained counterparts (1.92 ± 0.11, p = 0.002).ConclusionsUsing nondestructive 3D micro-CT, the simultaneous visualization of radiological and histopathological features is feasible.Relevance statement3D micro-CT data supports modern radiological and histopathological investigations of human bone tumor specimens. It has the potential for being an integrative part of clinical preoperative diagnostics.Key points• Matrix calcifications are a relevant diagnostic feature of bone tumors.• Micro-CT detects all clinically diagnostic relevant features of x-ray-stained chondrosarcoma.• Micro-CT has the potential to be an integrative part of clinical diagnostics.Graphical

FLAIR MRI sequence synthesis using squeeze attention generative model for reliable brain tumor segmentation

Manual segmentation of brain tumors using structural magnetic resonance imaging (MRI) is an arduous and time-consuming task. Therefore, automatic and robust segmentation will considerably influence neuro-oncological clinical trials by reducing excessive manual annotation time. Herein, we propose a deep learning model that automatically segments brain tumors even in cases of missing MRI sequences, which are common in practical clinical settings. To address this issue, we enhance a generative adversarial network (GAN) by incorporating a squeeze-and-excitation (SE) attention module into its generator and a PatchGAN into its discriminator. The SE module recalibrates channel responses by explicitly modeling interdependencies, enabling the network to focus on critical regions such as tumor areas. Our proposed generative model is optimized using a combination of adversarial, structural similarity, and mean absolute error losses to synthesize missing MRI sequences more effectively. This enhancement allows our model to synthesize the missing MRI sequence (fluid attenuated inversion recovery [FLAIR]) by leveraging information from other available sequences (T1-weighted, T2-weighted, or contrast-enhanced T1-weighted [T1ce]). For the segmentation task, we employ an optimized nnU-Net model, which is trained using existing sequences and evaluated using both available and synthesized sequences (including missing ones), mimicking real-world scenarios where often only limited MRI sequences are available or usable. Our findings reveal a notable enhancement in brain tumor segmentation, as indicated by a significant increase in overall the Dice similarity coefficient (DSC) from 0.688% (when FLAIR is missing) to 0.873% (when using synthesized FLAIR derived from T2). This improvement brings the segmentation performance closer to what was achieved when real FLAIR was available, where the DSC reaches 0.901%. Moreover, our synthesizing model was also tested on two additional datasets: the BraTS 2020 validation set and BraTS Africa 2023 training set, which produces results comparable to those of BraTS 2021, thereby proving its robustness and generalizability. In addition, the resulting tumor segmentations are subsequently employed to assess the response to treatment in cases where all sequences were available and when synthesis was employed, according to response assessment in neuro-oncology criteria.

Spatial interaction and functional status of CD68+SHP2+ macrophages in tumor microenvironment correlate with overall survival of NSCLC

BackgroundTumor-associated macrophages (TAMs) constitute a plastic and heterogeneous cell population of the tumor microenvironment (TME) that can regulate tumor proliferation and support resistance to therapy, constituting promising targets for the development of novel anticancer agents. Our previous results suggest that SHP2 plays a crucial role in reprogramming the phenotype of TAMs. Thus, we hypothesized that SHP2+ TAM may predict the treatment efficacy of non-small cell lung cancer NSCLC patients as a biomarker.MethodsWe analyzed cancer tissue samples from 79 NSCLC patients using multiplex fluorescence (mIF) staining to visualize various SHP-2+ TAM subpopulations (CD68+SHP2+, CD68+CD86+, CD68 + 206+, CD68+ CD86+SHP2+, CD68+ CD206+SHP2+) and T cells (CD8+ Granzyme B +) of immune cells. The immune cells proportions were quantified in the tumor regions (Tumor) and stromal regions (Stroma), as well as in the overall tumor microenvironment (Tumor and Stroma, TME). The analysis endpoint was overall survival (OS), correlating them with levels of cell infiltration or effective density. Cox regression was used to evaluate the associations between immune cell subsets infiltration and OS. Correlations between different immune cell subsets were examined by Spearman’s tests.ResultsIn NSCLC, the distribution of different macrophage subsets within the TME, tumor regions, and stroma regions exhibited inconsistency. The proportions of CD68+ SHP2+ TAMs (P < 0.05) were higher in tumor than in stroma. And the high infiltration of CD68+SHP2+ TAMs in tumor areas correlated with poor OS (P < 0.05). We found that the expression level of SHP2 was higher in M2-like macrophages than in M1-like macrophages. The CD68+SHP2+ subset proportion was positively correlated with the CD68+CD206+ subset within TME (P < 0.0001), tumor (P < 0.0001) and stroma (P < 0.0001).ConclusionsThe high infiltration of CD68+SHP2+ TAMs predict poor OS in NSCLC. Targeting SHP2 is a potentially effective strategy to inhibit M2-phenotype polarization. And it provides a new thought for SHP2 targeted cancer immunotherapy.

Brain tumor segmentation in MRI with multi-modality spatial information enhancement and boundary shape correction

Brain tumor segmentation is currently of a priori guiding significance in medical research and clinical diagnosis. Brain tumor segmentation techniques can accurately partition different tumor areas on multi-modality images captured by magnetic resonance imaging (MRI). Due to the unpredictable pathological process of brain tumor generation and growth, brain tumor images often show irregular shapes and uneven internal gray levels. Existing neural network-based segmentation methods with an encoding/decoding structure can perform image segmentation to some extent. However, they ignore issues such as differences in multi-modality information, loss of spatial information, and under-utilization of boundary information, thereby limiting the further improvement of segmentation accuracy. This paper proposes a multimodal spatial information enhancement and boundary shape correction method consisting of a modality information extraction (MIE) module, a spatial information enhancement (SIE) module, and a boundary shape correction (BSC) module. The above three modules act on the input, backbone, and loss functions of deep convolutional networks (DCNN), respectively, and compose an end-to-end 3D brain tumor segmentation model. The three proposed modules can solve the low utilization rate of effective modality information, the insufficient spatial information acquisition ability, and the improper segmentation of key boundary positions can be solved. The proposed method was validated on BraTS2017, 2018, and 2019 datasets. Comparative experimental results confirmed the effectiveness and superiority of the proposed method over state-of-the-art segmentation methods.

Phase II study to determine the anti-tumor activity and safety of simlukafusp alfa (FAP-IL2v) combined with atezolizumab in esophageal cancer.

Reported here are results from the esophageal squamous cell carcinoma (SCC) cohort of a Phase II, non-comparative, basket study, evaluating the anti-tumor activity and safety of FAP-IL2v plus atezolizumab in patients with advanced/metastatic solid tumors (NCT03386721). Eligible patients had an Eastern Cooperative Oncology Group performance status of 0-1; measurable metastatic, persistent, or recurrent esophageal SCC; progression on ≥1 prior therapy; and were checkpoint inhibitor naive. Patients received FAP-IL2v 10 mg plus atezolizumab 1200 mg intravenously every 3 weeks, or FAP-IL2v weekly for 4 weeks, then every 2 weeks, plus atezolizumab 840 mg intravenously every 2 weeks. Primary endpoint was investigator-assessed objective response rate (ORR). In the response-evaluable population (N=34), best confirmed ORR was 20.6% (95% confidence interval [CI]: 10.4-36.8) with a complete response (CR) seen in one patient and partial responses (PR) in six patients. Disease control rate was 44.1% (CR=2.9%; PR=17.6%; stable disease [SD]=23.5%) and median duration of response was 10.1 months (95% CI: 5.6-26.7). Median progression-free survival was 1.9 months (95% CI: 1.8-3.7). Analysis of response by PD-L1 expression (Ventana SP263) resulted in an ORR of 26.7 % for patients with PD-L1-positive tumors (tumor area positivity [TAP] cut-off ≥1%; n=15) and 7.1% for patients with PD-L1-negative tumors (TAP cut-off <1%; n=14). Overall, the treatment combination was tolerable and adverse events were consistent with the known safety profiles of each drug. FAP-IL2v plus atezolizumab demonstrated clinical activity and was tolerable in patients with previously treated esophageal SCC.

Recurrence Patterns after Radiotherapy for Glioblastoma with [(11)C]methionine Positron Emission Tomography-Guided Irradiation for Target Volume Optimization.

11C methionine (11C-MET) is increasingly being used in addition to contrast-enhanced MRI to plan for radiotherapy of patients with glioblastomas. This study aimed to assess the recurrence pattern quantitatively. Glioblastoma patients undergoing 11C-MET PET examination before primary radiotherapy from 2018 to 2023 were included in the analysis. A clinical target volume was manually created and fused with MRI-based gross tumor volumes and MET PET-based biological target volume. The recurrence was noted as an area of contrast enhancement on the first MRI scan, which showed progression. The recurrent tumor was identified on the radiological MR images in terms of recurrent tumor volume, and recurrences were classified as central, in-field, marginal, or ex-field tumors. We then compared the MET-PET-defined biological target volume with the MRI-defined recurrent tumor volume regarding spatial overlap (the Dice coefficient) and the Hausdorff distance. Most recurrences occurred locally within the primary tumor area (64.8%). The mean Hausdorff distance was 39.4 mm (SD 32.25), and the mean Dice coefficient was 0.30 (SD 0.22). In patients with glioblastoma, the analysis of the recurrence pattern has been mainly based on FET-PET. Our study confirms that the recurrence pattern after gross tumor volume-based treatment contoured by MET-PET is consistent with the FET-PET-based treatment described in the literature.

Abstract PO4-27-12: Increasing DAXX as a Novel Approach to Inhibit Breast Cancer Stem Cells and Estrogen Receptor-positive Tumor Recurrence

Abstract Background: Resistance to endocrine therapy (ET; tamoxifen, aromatase inhibitors, AI, or fulvestrant) in ER+ breast cancer (BC) could be due to survival of breast cancer stem cells (BCSCs). BCSCs contribute to relapse of ER+ BC. We discovered a novel and potent anti-BCSC gene, Death Associated Protein 6 (DAXX) through a pre-surgical biomarker window study combining ET plus a Notch inhibitor [MK-0752, a g-secretase inhibitor (GSI)]. We also found that ET enhances the BCSC population by decreasing DAXX protein levels. In this current study, we measured DAXX protein levels in ER+ PDX tumors and human tumor tissues treated with ET. We determined the mechanism by which ET regulates DAXX expression at the level of protein stability. The goal of this study was to identify novel therapeutic strategies to prevent ET-mediated degradation of the DAXX protein, eliminate BCSCs, and prevent ER+ recurrence. Methods: ER+ BC cell lines (MCF-7 and T47D), an ER+ PDX BCM 5097 tumor line, and human breast cancer tumor samples were used. The ER+ PDX tumor (BCM 5097) was implanted into NSG mice and passaged into female athymic, nude mice-supplemented with an estradiol capsule. After one week, the estradiol capsule was removed from 10 mice, to mimic the use of AI. The remaining 10 mice retained the estradiol capsule. Tumor area was measured weekly up to 50 weeks. Western blotting detected ERa, the stem cell factor Notch4, and DAXX levels. Immunohistochemistry (IHC) detected DAXX protein levels. ER+ human tumor samples were collected prior to and after neoadjuvant treatment with ET (N=11) or chemotherapy (N=14) and stained for the DAXX protein. Correlations were made between DAXX and Ki67. Full length and deletion mutants of DAXX were expressed in ER+ BC cells. BCSCs were measured using the mammosphere forming assay. Liquid chromatography followed by mass spectrometry were used to detect phosphorylated residues of DAXX in response to ET. Kinases that phosphorylate these residues on DAXX were identified using PhosphoSite.org. ER+ cells were treated with kinase inhibitors for AURKA (alisertib), AURKB (barasertib), CK1 (CK-IN-1), or CK2 (CX-4945) and DAXX protein was detected by western blotting. BCSC survival was measured using mammosphere forming assay. Based on results from the kinase inhibitor screen, barasertib was selected for pre-clinical testing in mice. ER+ MCF-7 xenograft tumors were treated with vehicle or barasertib in vivo up to 120 days. Results: DAXX protein levels decreased in ER+ PDX tumors in response to ET. Similar trends were detected in human tumor tissue after ET or chemotherapy alone. DAXX protein levels inversely correlated with Ki67 in ER+ human tumor samples. Analysis of DAXX deletion mutants demonstrated that amino acids 400-740 of the DAXX protein were required to inhibit BCSC survival. This region of the DAXX protein had high levels of phosphorylated residues in response to ET. Only the AURKB (barasertib) inhibitor increased DAXX protein expression and inhibited BCSCs in a DAXX-dependent manner. Barasertib inhibited growth of ER+ MCF-7 tumor xenografts compared to the vehicle control. After treatment ceased, tumor recurrence was measured up to 120 days. Regrowth of tumors was partially delayed in response to barasertib. Conclusions: ET decreased DAXX protein levels in ER+ PDX and human tumors. Downregulation of the DAXX protein by ET was through activation of AURKB and hyper-phosphorylation of DAXX which resulted in protein degradation and enhanced survival of BCSCs. Therefore, Inhibition of AURKB using barasertib partially restored DAXX expression, inhibited BCSCs, and delayed tumor recurrence. A combination approach of ET plus an AURKB inhibitor might be a novel therapeutic strategy to prevent ER+ breast cancer relapse by increasing DAXX in order to eradicate BCSCs. Support: Breast Cancer Research Foundation Citation Format: Clodia Osipo, Debra Wyatt, Kathy Albain. Increasing DAXX as a Novel Approach to Inhibit Breast Cancer Stem Cells and Estrogen Receptor-positive Tumor Recurrence [abstract]. In: Proceedings of the 2023 San Antonio Breast Cancer Symposium; 2023 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2024;84(9 Suppl):Abstract nr PO4-27-12.

Abstract PO5-17-01: Pre-treatment tumor infiltrating lymphocytes are associated with higher likelihood of pathologic complete response among black women with TNBC receiving neoadjuvant chemoimmunotherapy

Abstract Background: High risk, early-stage triple negative breast cancer (TNBC) is a heterogenous disease that is associated with early recurrence and high mortality, particularly among black women as compared to their white counterparts. Pathologic complete response (pCR) to neoadjuvant chemotherapy (NACT) is a strong-predictor of long-term disease-free survival in TNBC, and the KEYNOTE-522 trial demonstrated that the addition of immunotherapy (pembrolizumab) to NACT resulted in a higher likelihood of pathologic complete response (pCR) in high-risk early-stage TNBC. Following these findings, the standard of care has been to administer the K522 regimen (K522R) in the neoadjuvant setting for patients with high risk early-stage TNBC. However, our understanding of the clinical and tumor characteristics to prognosticate response to K522 are lacking, and additional real-world data is needed to better understand if these variables differ among race. Methods: We evaluated 76 patients who were treated with the K522R at our institution. There were slides available from 29 patients’ pre-treatment biopsies for pathology review. In the available slides, tumor infiltrating lymphocytes (TIL) were evaluated as the percentage of lymphocytes in the stroma within the tumor area. For the remaining cases that did not have available slides, these variables were retrieved from pathology reports and patients’ charts. Patient characteristics including age, race and body mass index (BMI) were acquired via retrospective chart review. These clinicopathologic variables were correlated with pCR, which was defined by the absence of invasive carcinoma in the breast and axillary lymph nodes at the time of surgery. Binary logistic regression analysis was performed to correlate the above variables with pCR versus residual disease (RD). Results: Seventy-six pre-treatment biopsy specimens treated with the K522R were evaluated. The patient population spanned a broad spectrum of age, body habitus, and race, with mean age 55, mean BMI 28.3, and predominantly black (over 60 percent) population. At the time of analysis, 64 of the 76 patients had completed the K522R and subsequently undergone surgery at our institution. Of the 64 patients who had undergone definitive surgery, 31 (48.4%) achieved pCR. In univariate analysis, pre-treatment TIL was significantly associated with attainment of pCR, with TIL of 28.5% (± 19.1) in patients who achieved pCR versus 9.73% (± 9.40) in those who had RD (95% CI 1.03-1.21, p=0.014*). When TIL was further stratified by race, mean percentage of TIL was significantly higher among black women who achieved pCR (27.5% ± 4.7) compared to black women with RD (12.2% ± 3.05) (95% CI 0.021 – 0.197, p=0.016*). Additionally, mean percentage of TIL was higher overall among black women when compared to the white patients in our cohort, though this finding was not statistically significant (p=0.252). Conclusion: Our real-world data demonstrates high levels of pre-treatment TIL are significantly associated with achievement of pCR in patients with TNBC treated with the K522 regimen. When TIL was further stratified by race, black patients were found to have higher TIL than white patients. Within the black population, a statistically significant difference in TIL percentage was found in those achieving pCR compared to those with RD. It is well understood that black women often have poorer breast cancer outcomes than white women, and our finding of higher TIL percentage among this population, along with the significant association between TIL and attainment of pCR with chemoimmunotherapy, could have important implications for optimization of therapy. Further exploration of this phenomenon in larger, diverse breast cancer populations is warranted. Citation Format: Sarah Wood, Ji-Hoon Lee, Yuan Gao, Xiaoxian Li, Jane Meisel. Pre-treatment tumor infiltrating lymphocytes are associated with higher likelihood of pathologic complete response among black women with TNBC receiving neoadjuvant chemoimmunotherapy [abstract]. In: Proceedings of the 2023 San Antonio Breast Cancer Symposium; 2023 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2024;84(9 Suppl):Abstract nr PO5-17-01.

Abstract PO5-15-12: Spatial immune correlates of response to eribulin and pembrolizumab in metastatic triple negative breast cancer (mTNBC) on the ENHANCE1 trial

Abstract Background: PD-L1 is the only approved biomarker for pembrolizumab in metastatic breast cancer for response to combination chemo-immunotherapy. As it is not predictive of response in all cases, additional biomarkers are needed. Previously we have demonstrated that stromal tumor infiltrating lymphocytes (sTILs) are associated with response to therapy in patients treated with front-line combination chemoimmunotherapy on the ENHANCE-1 study with eribulin and pembrolizumab. However, sTILs was not predictive of response in patients treated with prior lines of chemotherapy in the metastatic setting. We used multiplexed immunofluorescence on whole slide images to characterize associations between specific immune populations and outcomes in patients treated prospectively on the ENHANCE-1 study. Methods: ENHANCE-1 was a single arm phase Ib/II trial which evaluated the efficacy and safety of eribulin and pembrolizumab in 167 patients (pts) with mTNBC who had received 0-2 prior lines of therapy (66 pts in the first line setting [stratum 1] and 101 pts with 1-2 prior lines of therapy [stratum 2]). 138 patient samples were evaluable for our study: 58 samples from stratum 1 and 80 samples from stratum 2. Objective response rate (ORR) was defined as percentage of pts with either complete response (CR) or partial response (PR) by RECIST 1.1. The ORR was 25.8% in stratum 1 and 22.5% in stratum 2 for the 138 patients analyzed. We utilized whole tissue sections and quantitative multiplexed immunofluorescence (qmIF) stained with: CD4, FoxP3, CD8, CD56 and pancytokeratin to characterize T-cells, NK cells and tumor cells. Halo (Indica labs) was used to segment and threshold cells for positive markers as well as to identify tumor and stromal tissue areas. Results: We found that the ratio of CD8+ to CD4+FoxP3+ T-cells were associated with response, irrespective of stratum (p=0.005). As biopsies were not required immediately prior to enrollment on ENHANCE-1, we also evaluated samples based on prior number of treatments since biopsy to enrollment. We found that only 58/138 patient samples evaluated were obtained without intervening treatment: 35 out of 58 from stratum 1 and 12 out of 80 from stratum 2. When samples were evaluated by stratum and the timing of tissue acquisition we found the ratio of CD8+ to CD4+FoxP3+ T-cells was more significantly associated with response (&amp;lt; 0.001) in patients whose sample were collected prior to enrollment, regardless of patient stratum. The ratio was not predictive in samples taken prior to treatments before enrollment. In addition, we found stromal and intratumoral CD8+ T-cell density is associated with response (p=0.02 and p=0.03 respectively) across both stratum. We did not find any significant changes assessed by qmIF in patient samples which had intervening treatment between sample collection and enrollment onto ENHANCE-1 trial. Conclusion: In this population of patients with mTNBC treated prospectively with eribulin and pembrolizumab, we find that a higher ratio of CD8+ to CD4+FoxP3+ T-cells and stromal and intratumoral CD8+ T-cell density is associated with response in patients with biopsy samples obtained prior to enrollment without intervening treatments after sample collection. The tumor microenvironment on patient samples obtained before one or more lines of therapy prior to enrollment on study are not predictive of response to treatment. Further characterization of the TME via quantitative immunofluorescence is ongoing. This study was funded by Eisai Citation Format: Matthew Kearney, Hua Guo, Rami Vanguri, Qi Wang, Eileen Connolly. Spatial immune correlates of response to eribulin and pembrolizumab in metastatic triple negative breast cancer (mTNBC) on the ENHANCE1 trial [abstract]. In: Proceedings of the 2023 San Antonio Breast Cancer Symposium; 2023 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2024;84(9 Suppl):Abstract nr PO5-15-12.

Abstract PO3-25-07: Characterization of tertiary lymphoid structures and its association with response to immune checkpoint inhibitors in triple negative breast cancer using spatial transcriptomics

Abstract Background Tertiary lymphoid structures (TLS) are ectopic lymphoid organs playing a role in adaptive antitumor immune response. They were shown to be associated with favorable outcome and appears to be a promising biomarker for response to immune checkpoint inhibitors (ICI). Yet, there is no consensus for their detection and quantification. Here we aimed to derive a specific TLS signature using high resolution spatial transcriptomics data from a large series of triple negative breast cancer (TNBC) samples and to assess its clinical relevance including response to ICI. Methods Spatial transcriptomics (ST) was performed on a series of 94 early-stage TNBC surgical samples with detailed clinicopathological and outcome data. TLS and tumor infiltrating lymphocytes (TILs) were scored using hematoxylin and eosin and double immunohistochemistry (CD3/CD20) stained slides by a dedicated breast pathologist. Regression based on morphological annotations and deconvolution methods estimated the fraction of gene expression related to TLS in each ST spot allowing to derive specific TLS signature. Its prognostic and predictive value of response to ICI was assessed using publicly available breast cancer (METABRIC, SCAN-B, and I-SPY2) and other tumor type datasets treated with ICI (Bareche et al. Ann Oncol, 2022) from bulk gene expression data. Results Deconvolution of the TLS compartments using the ST gene expression data showed that TLS are enriched in all B cell subsets, CD4+ (central) memory and naïve T cells, as well as mast cells. A functional analysis showed an enrichment of ‘vascular endothelial cell proliferation’, ‘mitotic G2/M transition checkpoint’, ‘V/D/J recombination’ and ‘regulation of cell chemotaxis to fibroblast growth factor’ suggesting that TLS aggregates are associated with angiogenesis, immune cell proliferation, adaptative humoral response and tissue remodeling. A comparison of gene expression data between TLS and non-aggregated TILs led to the development of a specific TLS gene signature comprising B and T cell-specific genes, immunoglobulin genes as well as genes associated with TLS initiation. Its projection on tumor slides overlapped with the regions annotated as TLS by the pathologist, demonstrating its specificity for TLS detection. As expected, the highest levels of the TLS signature were observed in the immunomodulatory TNBC molecular subtype and fully inflamed tumors, whereas the lowest levels were observed in the mesenchymal molecular subtype and immune desert tumors (p&amp;lt; 0.05). Of note, high levels of the TLS signature were associated with better prognosis in TNBC patients from METABRIC (p=6.5 10−5) and SCAN-B datasets (p=1.6 10−3) as well as with higher pathological complete response rates in all breast cancer patients treated with neoadjuvant pembrolizumab in the I-SPY2 study (p=0.026). Similar results were found in other tumor types treated with immunotherapy in the metastatic setting including metastatic melanoma, pancreatic and bladder cancers (PFS, p=6 10−6). Of interest, the TLS signature outperformed the predictive value of other immune-related signatures including TILs suggesting a key role of TLS in obtaining a sustainable, adaptive antitumor immune response in the vicinity of the tumor area. Conclusion By leveraging the potential of spatial transcriptomics, we have successfully developed a unique TLS gene signature that demonstrates a strong correlation with the response to ICI in breast cancer and various other tumor types. This TLS gene signature outperforms other immune biomarkers, underscoring the pivotal role of TLS in eliciting a robust antitumor immune response. The universality of this TLS signature makes it a potent biomarker capable of identifying patients who would benefit from immunotherapy, pending further validation. Citation Format: Xiaoxiao Wang, David Venet, Frédéric Lifrange, Denis Larsimont, Mattia Rediti, Linnea Stenbeck, Floriane Dupont, Ghizlane Rouas, Andrea Joaquin Garcia, David Gacquer, Ligia Craciun, Laurence Buisseret, Nayanika Bhalla, Yuvarani Masarapu, Kim Thrane, Eva Gracia Villacampa, Lovisa Franzén, Sami Saarenpää, Linda Kvastad, Joakim Lundeberg, Françoise Rothé, Christos Sotiriou. Characterization of tertiary lymphoid structures and its association with response to immune checkpoint inhibitors in triple negative breast cancer using spatial transcriptomics [abstract]. In: Proceedings of the 2023 San Antonio Breast Cancer Symposium; 2023 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2024;84(9 Suppl):Abstract nr PO3-25-07.

Abstract PO1-19-10: Durvalumab + datopotamab deruxtecan in patients with PD-L1 positive advanced/metastatic triple-negative breast cancer: Arm 8 of the phase 1b/2, open label, platform BEGONIA study

Abstract Background: Patients (pts) with advanced/metastatic triple-negative breast cancer (a/mTNBC) have limited treatment options and poor prognosis. Immune checkpoint inhibitors combined with chemotherapy is the standard of care for pts with PD-L1 positive tumors; still, most pts progress within a year, highlighting a need for new treatments. BEGONIA is an ongoing Simon 2-stage, multicenter, multi-arm platform study evaluating the safety and efficacy of durvalumab (D), an anti–PD-L1 monoclonal antibody, with or without paclitaxel, in combination with novel oncology therapies as first-line treatment for a/mTNBC (NCT03742102). Datopotamab deruxtecan (Dato-DXd) is an antibody-drug conjugate (ADC) consisting of a humanized anti-trophoblast cell surface antigen 2 (TROP2) IgG1 monoclonal antibody linked to a topoisomerase I inhibitor payload via a plasma stable, tumor selective, tetrapeptide-based cleavable linker. TROP2 is broadly expressed on breast and other epithelial tumors and Dato-DXd monotherapy showed antitumor activity in heavily pretreated mTNBC pts (Bardia SABCS 2022 P6-10-03). Pts treated with Dato-DXd+D in Arm 7 of BEGONIA showed a 74% objective response rate (ORR) with median 7.2 months follow-up (Schmid SABCS 2022 PD11-09). Although responses were observed in both PD-L1–high and –low-expressing tumors, most pts (87%) had PD-L1–low-expressing tumors. In Arm 8 of BEGONIA, pts determined to have PD-L1 positive tumors by pre-existing/local testing will be recruited and treated with Dato-DXd+D to evaluate efficacy and safety in a PD-L1–high population. Methods: Eligible female pts are aged ≥18 years with untreated unresectable, locally advanced or mTNBC; ≥6 months between completion of treatment for earlier-stage breast cancer and recurrence of distant disease; ≥12 months since prior taxane therapy; ECOG PS 0/1; adequate organ function; and ≥1 nonirradiated measurable lesion. For inclusion in Arm 8, a PD-L1 positive tumor as determined by local immunohistochemistry (IHC) testing is required (either pre-existing or obtained during prescreening). Exclusion criteria for Arm 8 are clinically significant corneal disease; history or suspicion of interstitial lung disease/pneumonitis; underlying pulmonary disorder; prior exposure to immune-mediated therapy; or prior treatment with an ADC containing a topoisomerase I inhibitor. Arm 8 will evaluate Dato-DXd (6 mg/kg) + D (1120 mg) given intravenously every 3 weeks until disease progression or unacceptable toxicity. Tumors will be assessed per RECIST v1.1 every 6 weeks for 48 weeks, then every 12 weeks thereafter. A safety run-in will not occur for Arm 8, as Dato-DXd+D was evaluated in Arm 7 and was tolerable with no DLTs reported. Part 1 of Arm 8 will enroll 30 pts. The primary endpoint of Part 1 is safety and tolerability. A futility analysis will be performed with an option to expand Arm 8 to Part 2, where an additional 27 pts will be enrolled if expansion criteria are met. The primary endpoint for Part 2 is ORR. Secondary endpoints include ORR (Part 1 only), testing for antidrug antibodies and treatment pharmacokinetics (Part 1 only), duration of response (DoR), progression-free survival (PFS), and overall survival (OS). ORR will be summarized with descriptive statistics and 95% Clopper-Pearson confidence intervals. Kaplan-Meier analysis will be used for DoR, PFS, and OS. All tumor response and survival endpoints will be based on investigator assessments. Additional PD-L1 testing with the VENTANA PD-L1 (SP263) Assay will be performed on pretreatment tumor samples; high expression is defined as ≥10% of the tumor area populated by PD-L1–expressing tumor or immune cells. TROP2 expression will be assessed by IHC. Enrollment is ongoing. Funding: AstraZeneca/Daiichi Sankyo Citation Format: Peter Schmid, Cynthia Ma, Robert Huisden, Ross Stewart, Katrin Heider, Petra Vuković, Neelima Denduluri. Durvalumab + datopotamab deruxtecan in patients with PD-L1 positive advanced/metastatic triple-negative breast cancer: Arm 8 of the phase 1b/2, open label, platform BEGONIA study [abstract]. In: Proceedings of the 2023 San Antonio Breast Cancer Symposium; 2023 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2024;84(9 Suppl):Abstract nr PO1-19-10.

Abstract PO4-26-01: Computational pathology: Revolutionizing diagnostics and clearing the way for precision medicine

Abstract While targeted cancer therapies often rely on subjective and semi-quantitative visual assessment of protein biomarkers by pathologists through immunohistochemically stained tissue, the transformative force of computational pathology is reshaping healthcare by unleashing unprecedented diagnostic accuracy and unlocking personalized treatments. In recent years, we have established a large integrated computational pathology unit to foster collaboration between interdisciplinary teams of computer scientists, pathologists, molecular biologists, and data scientists. This integration of cutting-edge technologies enabled us to develop a computational pathology approach called Quantitative Continuous Scoring (QCS). QCS deploys the power of Deep Learning (DL) to provide objective and continuous expression data of biomarkers in digitized IHC whole slide images (WSI), particularly of proteins expressed at low levels. While manual scoring of IHC WSIs is limited by subjectivity and semi-quantitative assessment of protein expression, QCS overcomes these limitations with an unprecedented accuracy. QCS utilizes two DL-based algorithms, which we developed fully supervised by using pathologist input as the reference standard. These algorithms identify invasive tumour areas and segment each tumour cell across the WSI into cell nuclei, cytoplasm and membrane. Based on an accurate subcellular segmentation, we can compute biomarker expression, on a continuous scale, as mean Optical Density (OD) in each subcellular compartment based on the Hue-Saturation-Density (HSD) model. Therefore, this approach enables precise detection of the low biomarker expression range with single-cell resolution. Importantly, it also allows the computation of the spatial distribution of tumour cells across the WSI. We have successfully used QCS to drive the selection of antibody clones for IHC assays and to delineate the mode of action and PK/PD mechanisms. Of note, the combination of assessing continuous target expression and capturing the spatial distribution of tumor cells has provided surrogate markers to predict potential bystander activity of antibody drug conjugates (ADCs). This approach outperformed traditional pathologist scoring in identifying patient populations having maximum treatment benefit through retrospective analysis of multiple clinical trials. At present, all computational pathology approaches are developed based on conventional IHC assays that have been optimized for manual scoring. Importantly, we draw a vision in which the assay serves as a critical catalyst for unleashing the full potential of computational pathology by providing high-quality, standardized data inputs. We suggest an approach utilizing orthogonal methods as a reference standard to develop highly sensitive IHC assays, capable of detecting even subtle molecular and cellular changes with precision and exhibiting exceptional specificity for accurately identifying and distinguishing target biomarkers from background noise. In summary, we here describe and discuss a computational pathology-based approach for precise biomarker quantification and superior patient selection with broad applicability and the potential to transform the very fabric of how we diagnose and treat cancer. Citation Format: Mark Gustavson, Markus Schick, Ansh Kapil, Anatoliy Shumilov, Carl Barrett, Hadassah Sade. Computational pathology: Revolutionizing diagnostics and clearing the way for precision medicine [abstract]. In: Proceedings of the 2023 San Antonio Breast Cancer Symposium; 2023 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2024;84(9 Suppl):Abstract nr PO4-26-01.

Abstract PO4-15-03: Quantitative Measurement of TROP2 via Chromogenic Immunohistochemistry in Breast Cancer

Abstract Sacituzumab govitecan (SG) is an antibody-drug conjugate that targets human trophoblast cell-surface antigen 2 (TROP2), which is expressed in over 90% of breast cancer cases (Zaman et al, 2019). By delivering the cytotoxic SN-38 (topoisomerase I inhibitor) to TROP2 expressing breast cancer cells, SG showed promising antitumor activities in clinical trials and is now an approved treatment for triple-negative breast cancer (TNBC) and hormone receptor (HR)-positive HER2-negative breast cancer in the metastatic setting. Despite the prevalent expression of TROP2 in breast cancer, the objective response rates reported from clinical trials were about 30%, indicating the need for a diagnostic test that can identify which patients are likely to benefit from therapy. Although the drug is approved without a companion diagnostic assay, recent data from the TROPiCS-02 trial has shown that TROP2-low (H-score &amp;lt; 100) showed a non-significant hazard ratio for benefit from SG. In the same study, patients treated with SG with H-score &amp;gt;100 showed a significant hazard ratio for benefit compared to physician’s choice (Tolaney et al, ASCO 2023). This suggests that TROP2 expression level is associated with SG response and that a threshold for TROP2 expression level may aid patient selection. Although over 90% of breast cancer patients were considered TROP2-positive by IHC, the expression level of TROP2 was never quantitatively assessed in large breast cancer cohorts. Here we describe a quantitative chromogenic immunohistochemistry (IHC) assay with a cell line standard. Mass spectrometry was used to measure TROP2 peptide concentrations in the six standard cell lines, and the correlation between the mass spectrometry and IHC data for each cell line was then used to convert chromogenic signals to concentrations of TROP2 protein (fmol/mm2). The antibody used in this assay was rigorously validated, and the antibody concentration was optimized for the best signal-to-noise ratio. The optical density (OD) of chromogenic staining was measured using QuPath 0.4.3 (Qymia extension) by identifying the tumor area via object classifiers and manual editing and then calculating the area-normalized sum of OD. Collectively, this assay can measure up to 29.1 fmol/mm2 of TROP2. By applying this assay to two serial retrospective primary breast cancer cohorts from Yale University, we quantitatively measured TROP2 expression levels in 332 clinical cases. Not surprisingly, over 90% of cases showed some chromogenic signal, with a median TROP2 concentration of 2.1 fmol/mm2 and a maximum of 10.5 fmol/mm2. TROP2 expression levels showed no significant association with clinicopathologic characteristics including race, stage, BRCA mutation status, molecular subtype, HER2 IHC levels, and outcome. Further work is underway to optimize the assay toward the goal of determination of whether there is a quantitatively definable threshold for TROP2 expression below which patients are unlikely to benefit from SG or other TROP2-targeted therapies. Citation Format: Mengni He, Matthew Liu, Thazin Aung, Sneha Burela, Katherine Bates, Charles Robbins, David Rimm. Quantitative Measurement of TROP2 via Chromogenic Immunohistochemistry in Breast Cancer [abstract]. In: Proceedings of the 2023 San Antonio Breast Cancer Symposium; 2023 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2024;84(9 Suppl):Abstract nr PO4-15-03.

Abstract PO4-26-09: The Advantage of Artificial-Intelligence in HER2 IHC 0 and 1+ Scoring in Breast Cancer

Abstract Background: Trastuzumab deruxtecan has substantially changed the treatment of HER2-low breast cancer, emphasizing the need for accurate differentiation between HER2 immunohistochemistry (IHC) scores of 0 and 1+. However, the current accuracy of HER2 IHC 0 and 1+ scoring in real-world is inadequate. Artificial intelligence (AI) has emerged as a potential solution to improve interpretation accuracy. We developed an AI algorithm based on whole slide images (WSI) to quantitatively assess HER2 expression and its role in interpreting HER2 IHC scores of 0 and 1+. Methods: Our three-phase AI analysis framework involved segmenting tumor areas (excluding ductal carcinoma in situ), detecting and classifying tumor cells based on membrane staining patterns, and grading HER2 IHC scores according to the 2018 ASCO/CAP HER2 guideline. The AI tool was trained using 6012 patches annotated by experienced pathologists. Performance evaluation was conducted using a test dataset comprising 265 slides. A total of 141 HER2 IHC slides (27 IHC 0 and 114 IHC 1+) from patients diagnosed with invasive breast cancer at Fudan University Shanghai Cancer Center in 2021 were included. Two pretrained expert pathologists independently rescored the HER2 slides, followed by analysis using the AI tool. All inconsistent cases were also reviewed by a third senior pathologist. Interobserver agreement between the pathologists and concordance between the pathologists and the AI interpretation results were assessed. We also explored potential ranges where HER2 interpretation by pathologists exhibited inconsistency or inaccuracy. Results: The HER2 AI algorithm showed high performance in interpreting all levels of HER2 expression, with an overall kappa value of 0.85. For HER2 IHC 0 and 1+ cases, the AI model demonstrated high sensitivities (0.839 and 0.914) and specificities (0.983 and 0.890) (Table 1). After the rescoring process, 51 cases were reclassified as IHC 0 and 90 cases as IHC 1+. The overall agreement rate between the historical and re-scoring results was 73.05% (103/141). The agreement rate between the AI and re-scoring results was 91.49% (129/141) (Table 2), indicating comparable interpretation capabilities between the AI model and well-trained pathologists. The interobserver agreement between the two pathologists was 83.69% (118/141), with agreement rates of 88.23% (45/51) for IHC 0 and 81.11% (73/90) for IHC 1+. Analyzing the inconsistent cases (n=12) between IHC 0 and IHC 1+, we examined the percentage of weak and incomplete expression provided by the AI. In 9 out of 12 cases, the AI provided the same results as the third senior pathologist, suggesting that AI could assist in interpretation within this range. We identified a range of 2.83% to 24.98% as a "grey-zone," where even well-trained pathologists provided inconsistent results. Conclusion: Our study demonstrates the excellent performance of an AI-based tool for scoring HER2 IHC 0 and 1+. The AI model exhibits comparable capabilities to well-trained pathologists in interpreting HER2 expression. Additionally, we identified a "grey-zone" among pathologists, highlighting the limitations of manual subjective interpretation. AI assistance within this zone may help mitigate subjective variations. Table 1. Correlation between pathologist read and AI read of HER2 immunohistochemistry. Table 2. Correlation between pathologist rescoring and AI read of HER2 immunohistochemistry. Citation Format: Ming Li, Hong Lv, Yizhi Zhao, Chenglu Zhu, Hansheng Li, Mingzhen Lin, Wen-Tao Yang. The Advantage of Artificial-Intelligence in HER2 IHC 0 and 1+ Scoring in Breast Cancer [abstract]. In: Proceedings of the 2023 San Antonio Breast Cancer Symposium; 2023 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2024;84(9 Suppl):Abstract nr PO4-26-09.

Abstract PO5-06-06: Tumor/stromal expression of CD3/CD8/PD-1/PD-L1 and overall survival (OS) in patients (pts) with metastatic (met) HER2+ breast cancer (BC)

Abstract Background: The “Thousand Patient HER-2 database” project at Saint Vincent’s University Hospital (SVUH) Dublin contains a cohort of met HER2+ BC pts treated with trastuzumab, with OS ranging from short term to durable complete response (never relapsed). While the majority of pts progress on treatment, higher stromal tumor immune infiltrate has been associated with longer OS in met HER2+ BC. Using the SVUH database, we have identified a cohort of met HER2+ BC pts that received trastuzumab and have a broad OS range (0.3 months (mos) to 200.9 mos). This study examines the tumor and stromal levels of pan T cell marker CD3, cytotoxic T cell marker CD8, and immune checkpoints PD-L1 and PD-1 by immunohistochemistry (IHC) in primary and met samples from this cohort. Methods: Clinico-pathological data was available for formalin-fixed, paraffin-embedded biopsy specimens (n=45 primary, n=25 matched met biopsies). IHC staining was conducted for CD3 (Agilent IR50361-2), CD8 (Agilent IR62361-2), PD-L1, (Agilent M365329-2), and PD-1 (Roche 07099029001). A DAKO Link 48 Autostainer was utilised for staining, incorporating positive (tonsil tissue) and negative controls (isotype controls). Slide processing used an Aperio AT2 Digital Slide Scanner (Leica Biosystems), Aperio ImageScope 12.4 software (Leica Biosystems) and QuPath analysis software (University of Edinburgh). Following annotation of tumor areas, an algorithm was trained to identify immune cells and designate them as tumor or stromal. Data was expressed as the number of positively stained cells/mm2 tissue. A median cut-off was applied to denote “high” and “low” expression for CD3 and CD8. For PD-1 and PD-L1, samples with ≥ 1 stained cell/mm2 were designated as positive (pos) and samples with zero stained cells as negative (neg). The Kaplan Meier method was utilised for survival studies. A paired Student’s t test was utilised for primary vs metastatic site comparisons. Results: 51.1% of primary samples displayed high CD3 (23/45) and CD8 (23/45) expression in both the stromal and tumor compartments. Within the tumor compartment, 18.6% (8/43) of samples were pos for PD-L1 expression, and 57.8% (26/45) were pos for PD-1 expression. In the stromal compartment, 30.2% (13/43) of samples were pos for PD-L1 expression, and 68.9% (31/45) were pos for PD-1 expression. High tumor levels of CD3 (median OS CD3 high 113.4 mos vs CD3 low 7.9 mos, HR 0.2938 (95% CI 0.130-0.618), p=0.0012) and CD8 (median OS CD8 high 73.9 mos vs CD8 low 10.8 mos, HR 0.4764 (95% CI 0.238-0.954), p=0.0365), but not stromal levels of these markers, were associated with improved OS. There were no significant differences in CD3, CD8, PD-1 and PD-L1 levels between matched primary and met samples (p &amp;gt;0.05). Tumor, but not stromal, PD-L1 expression was associated with longer OS (HR 0.3120 (95% CI 0.146-0.667), p=0.0027). Interestingly, stromal PD-1 expression, but not tumor PD-1 expression, was also associated with longer OS (median OS PD-1 pos 64.7 mos vs. PD-1 neg 5.6 mos, HR 0.158 (95% CI 0.060-0.411), p=0.0002). Conclusion: Our results report a link between OS and tumor (CD3+, CD8+ and PD-L1+)/stromal (PD-1+) immune cell infiltrate in met HER2+ BC patients treated with trastuzumab. Further expansion of this preliminary dataset is warranted. Citation Format: Denis Collins, Janet McCormack, Laura Ivers, Jose Javier Berenguer-Pina, Jo Ballot, Cecily Quinn, Darko Skrobo, Alex Eustace, Naomi Walsh, Aurelie Fabre, John Crown. Tumor/stromal expression of CD3/CD8/PD-1/PD-L1 and overall survival (OS) in patients (pts) with metastatic (met) HER2+ breast cancer (BC) [abstract]. In: Proceedings of the 2023 San Antonio Breast Cancer Symposium; 2023 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2024;84(9 Suppl):Abstract nr PO5-06-06.

[Zinc Suppresses Colorectal Cancer Development through Cell-mediated Immunity].

Zinc is one of the essential trace elements, and is involved in various functions in the body. Zinc deficiency is known to cause immune abnormalities, but the mechanism is not fully understood. Therefore, we focused our research on tumor immunity to elucidate the effect of zinc on colorectal cancer and its mechanisms. Mice were treated with azoxymethane (AOM) and dextran sodium sulfate (DSS) to develop colorectal cancer, then the relationship between zinc content in the diet and the number and area of tumors in the colon was observed. The number of tumors in the colon was significantly higher in the no-zinc-added diet group compared to the normal zinc intake group, and about half the number in the high-zinc-intake group compared to the normal-zinc-intake group. In T-cell-deficient mice, the number of tumors in the high-zinc-intake group was similar to that in the normal-zinc-intake group, suggesting that the inhibitory effect of zinc was dependent on T cells. Furthermore, we found that the amount of granzyme B transcript released by cytotoxic T cells upon antigen stimulation was significantly increased by the addition of zinc. We also showed that granzyme B transcriptional activation by zinc addition was dependent on calcineurin activity. Collectively, we have shown that zinc exerts its tumor-suppressive effect by acting on cytotoxic T cells, the center of cellular immunity, and that it increases the transcription of granzyme B, one of the key molecules involved in tumor immunity. In this symposium, we would like to introduce our latest data on the relationship between zinc and tumor immunity.

HyperArc performance in radiotherapy and its correlations with number and volume of multiple brain metastases

ObjectiveTo assess the performance and advantages of HyperArc for radiotherapy of multiple brain metastases with dosimetric parameters with respect to coplanar volumetric modulated arc radiotherapy (c-VMAT), and characterize implicit correlations between tumor features and dosimetric parameters. MethodsThis retrospective study involved 40 patients with multiple brain metastases (4-16 tumors, 12.8-240.8 cm3) who received simultaneous radiotherapy at the Department of Radiation Oncology, Shenzhen People's Hospital from January 2019 to December 2022. Both HyperArc and c-VMAT plans were designed by the same and qualified physicist using the Eclipse system with Truebeam. A single isocenter and a 6 MV flattening filter-free (6FFF) photon beam were used for radiotherapy of multiple brain metastases in each plan. Dosimetric parameters of tumors and organs at risk (OARs) were compared between HyperArc and c-VMAT plans. Correlations between tumor features (number and volume) and dosimetric parameters were revealed and analyzed. Furthermore, monitor units (MUs) of both plan types were recorded to assess rays utilization and delivery efficiency. ResultsCompared to c-VMAT plans, HyperArc plans achieved higher maximum dose (Dmax) (5.23%, t=7.87, P<0.01), but lower minimum dose (Dmin) (3.94%, t=-2.12, P=0.04) and mean dose (Dmean) (1.05%, t=-3.29, P<0.01) for planning gross tumor volumes (PGTVs). The conformity index (CI), homogeneity index (HI), gradient index (GI) and R50% of PGTVs with HyperArc were better than those with c-VMAT, with the improvements of 20.78%, 1.68%, 19.83% and 36.20%, respectively (P<0.01). The dosimetric parameters of OARs were significantly improved in HyperArc plans compared to c-VMAT plans. Specifically, the Dmax and the Dmean to the brainstem decreased by 16.14% and 11.37%, respectively. The Dmax for eye_L decreased by 16.88%, for eye_R decreased by 11.67%, for optical nerve_L decreased by 12.56%, and for chiasm decreased by 18.12%. Few correlations were observed between the differences of CI/ HI/ GI/ R50% and the number of PGTVs between the two plan types. Whereas, regression analysis indicated that the differences of CI/ GI/ R50% were negatively correlated with the volume of PGTVs, respectively. Moreover, although HyperArc plans reduced the MUs by 4.74% compared to c-VMAT, no significant difference was observed (P>0.05). ConclusionsThis study demonstrates the promising performance of HyperArc for radiotherapy of multiple brain metastases, including better dose conformity for the tumors, more rapid dose drop and less dose spillage outside the tumors area, effective reduction of dose bridges among close tumors, and sparing OARs. It also reveals the correlations between the number or volume of tumors and dose parameters, which can help optimize the use of HyperArc and predict clinical benefits.

Tracing tumor heterogeneity of pleomorphic carcinoma of the lung

BackgroundPulmonary pleomorphic carcinoma (PPC) is an aggressive and highly heterogeneous non-small-cell lung carcinoma whose underlying biology is still poorly understood. MethodsForty-two tumor areas from 20 PPC patients were microdissected, including 39 primary tumors and 3 metastases and the histologically distinct components were subjected to whole exome sequencing (WES) separately. We further performed in silico analysis of microdissected bulk RNAseq and methylation data of 28 samples from 14 PPC patients. We validated our findings using immunohistochemistry. ResultsThe epithelial and the sarcomatoid components of PPCs shared a large number of genomic alterations. Most mutations in cancer driver genes were clonal and truncal between the two components of PPCs suggesting a common ancestor. The high number of alterations in the RTK-RAS pathway suggests that it plays an important role in the evolution of PPC. The metastases morphologically and genetically resembled the epithelial or the sarcomatoid components of the tumor.The transcriptomic and epigenetic profiles of the sarcomatoid components of PPCs with matched squamous-like or adenocarcinoma-like components differed from each other and they shared more similarities to their matched epithelial components. NCAM1/CD56 was preferentially expressed in the sarcomatoid component of squamous-like PPCs, whereas CDH1/E-Cadherin expression was downregulated in the sarcomatoid component of most PPCs. ConclusionLUAD-like PPCs are mainly driven by RTK-RAS signaling, whereas epithelial-mesenchymal transition programs as highlighted by increased NCAM1 and decreased CDH1 expression govern the epithelial-sarcomatoid transition between the clonally related tumor components. Several alterations in PPCs pinpoint therapeutic opportunities.

Grade Heterogeneity in High-Grade Urothelial Carcinomas: Does It Have an Impact on the Survival of Patients With Intermediate/High-Risk Nonmuscle-Invasive Bladder Cancer Who Received Adequate Adjuvant Bacillus Calmette-Guérin Therapy?

We aimed to compare recurrence-free survival (RFS) and progression-free survival (PFS) of the patients with pure high-grade (HG) vs mixed-grade (MG) nonmuscle-invasive bladder cancer who received adequate bacillus Calmette-Guérin therapy. We conducted a retrospective cohort analysis using data from an institutional database. The study included patients diagnosed with HG nonmuscle-invasive bladder cancer at the initial transurethral resection specimen between 2010 and 2020. The initial transurethral resection specimens of all patients were reevaluated by a dedicated uropathologist. The percentage of low-grade tumor areas accompanying HG areas was determined for each case. Time-to-event analysis was performed using the Kaplan-Meier method. RFS and PFS rates were compared between groups. Of the 203 patients enrolled in the study, 69 (34%) had MG tumors. Recurrence was observed in 41 out of 134 patients (30.6%) in the HG group and in 19 out of 69 patients (27.5%) in the MG group. The 36-month RFS rates were 69% (CI: 62-77) and 72% (CI: 62-83) for the HG-urothelial carcinoma (UC) and MG-UC groups, respectively. The RFS rates were similar between groups (log-rank, P = .58). Progression was observed in 22 out of 134 patients (16.4%) in the HG group and in 4 out of 69 patients (5.8%) in the MG group. The 36-month PFS rates were 84% (CI: 77-90) and 94% (CI: 89-100) for the HG-UC and MG-UC groups, respectively. The pure HG-UC group had a worse PFS than the MG-UC group (log-rank, P = .042). Multivariate analysis demonstrated that age and tumor grade were significant risk factors for the development of progression. The indication of MG-UC category separately from pure HG carcinomas in the pathology report seems to be an important issue that can guide patient management. In this way, both more accurate risk classification and more accurate patient counseling can be performed. More importantly, the treatment plan can be made more accurately. For more precise conclusions, our results should be supported by prospective studies with larger sample size.

Multi-level brain tumor classification using hybrid coot flamingo search optimization Algorithm Enabled deep learning with MRI images

ABSTRACT An innovative multi-level BT classification approach based on deep learning has been proposed in this article. Here, classification is accomplished using the SpinalNet, whose structure is optimized by the Hybrid Coot Flamingo Search Optimization Algorithm (CootFSOA). Further, a novel segmentation approach using CootFSOA-LinkNet is devised for isolating the tumour area from the brain image. Here, the input MRI images are fed into the Adaptive Kalman Filter (AKF) to denoise the image. In the segmentation process, LinkNet is used to separate the tumour region from the MRI image. CootFSOA is used to achieve structural optimization of LinkNet. The segmented image is then used to create several features, and the resulting feature vector is fed into SpinalNet to detect BT. CootFSOA is used in this instance as well to adjust the SpinalNet’s hyperparameters and achieve high detection accuracy. If a tumour is detected, second-level classification is carried out by employing the CootFSOA-SpinalNet to classify the input image into several types, such as gliomas, pituitary tumours, and meningiomas. Moreover, the efficacy of the CootFSOA-SpinalNet has been examined considering accuracy, True Positive Rate (TPR), and True Negative Rate (TNR) and has recorded superior values of 0.926, 0.931, and 0.925, respectively.