Peritumoral Tissue Research Articles

Single-cell transcriptome analysis identifies a unique tumor cell type producing multiple hormones in ectopic ACTH and CRH secreting pheochromocytoma.

Ectopic Cushing's syndrome due to ectopic ACTH&CRH-secreting by pheochromocytoma is extremely rare and can be fatal if not properly diagnosed. It remains unclear whether a unique cell type is responsible for multiple hormones secreting. In this work, we performed single-cell RNA sequencing to three different anatomic tumor tissues and one peritumoral tissue based on a rare case with ectopic ACTH&CRH-secreting pheochromocytoma. And in addition to that, three adrenal tumor specimens from common pheochromocytoma and adrenocortical adenomas were also involved in the comparison of tumor cellular heterogeneity. A total of 16 cell types in the tumor microenvironment were identified by unbiased cell clustering of single-cell transcriptomic profiles from all specimens. Notably, we identified a novel multi-functionally chromaffin-like cell type with high expression of both POMC (the precursor of ACTH) and CRH, called ACTH+&CRH + pheochromocyte. We hypothesized that the molecular mechanism of the rare case harbor Cushing's syndrome is due to the identified novel tumor cell type, that is, the secretion of ACTH had a direct effect on the adrenal gland to produce cortisol, while the secretion of CRH can indirectly stimulate the secretion of ACTH from the anterior pituitary. Besides, a new potential marker (GAL) co-expressed with ACTH and CRH might be involved in the regulation of ACTH secretion. The immunohistochemistry results confirmed its multi-functionally chromaffin-like properties with positive staining for CRH, POMC, ACTH, GAL, TH, and CgA. Our findings also proved to some extent the heterogeneity of endothelial and immune microenvironment in different adrenal tumor subtypes.

Magnetic Resonance Imaging-Based Radiomics Features Associated with Depth of Invasion Predicted Lymph Node Metastasis and Prognosis in Tongue Cancer.

BackgroundAdequate safe margin in tongue cancer radical surgery is one of the most important prognostic factors. However, the role of peritumoral tissues in predicting lymph node metastasis (LNM) and prognosis using radiomics analysis remains unclear.PurposeTo investigate whether magnetic resonance imaging (MRI)‐based radiomics analysis with peritumoral extensions contributes toward the prediction of LNM and prognosis in tongue cancer.Study typeRetrospective.PopulationTwo hundred and thirty‐six patients (38.56% female) with tongue cancer (training set, N = 157; testing set, N = 79; 37.58% and 40.51% female for each).Field Strength/Sequence1.5 T; T2‐weighted turbo spin‐echo images.AssessmentRadiomics models (Rprim, Rprim+3, Rprim+5, Rprim+10, Rprim+15) were developed with features extracted from the primary tumor without or with peritumoral extensions (3, 5, 10, and 15 mm, respectively). Clinicopathological characteristics selected from univariate analysis, including MRI‐reported LN status, radiological extrinsic lingual muscle invasion, and pathological depth of invasion (DOI) were further incorporated into radiomics models to develop combined radiomics models (CRprim, CRprim+3, CRprim+5, CRprim+10, CRprim+15). Finally, the model performance was validated in the testing set. DOI was measured from the adjacent normal mucosa to the deepest point of tumor invasion.Statistical TestsChi‐square test, regression analysis, receiver operating characteristic curve (ROC) analysis, decision analysis, spearman correlation analysis. The Delong test was used to compare area under the ROC (AUC). P < 0.05 was considered statistically significant.ResultsOf all the models, the CRprim+10 reached the highest AUC of 0.995 in the training set and 0.872 in the testing set. Radiomics features were significantly correlated with pathological DOI (correlation coefficients, −0.157 to −0.336). The CRprim+10 was an independent indicator for poor disease‐free survival (hazard ratio, 5.250) and overall survival (hazard ratio, 17.464) in the testing set.Data ConclusionRadiomics analysis with a 10‐mm peritumoral extension had excellent power to predict LNM and prognosis in tongue cancer.

Spatial immunoprofiling of the intratumoral and peritumoral tissue of renal cell carcinoma patients

While the abundance and phenotype of tumor-infiltrating lymphocytes are linked with clinical survival, their spatial coordination and its clinical significance remain unclear. Here, we investigated the immune profile of intratumoral and peritumoral tissue of clear cell renal cell carcinoma patients (n = 64). We trained a cell classifier to detect lymphocytes from hematoxylin and eosin stained tissue slides. Using unsupervised classification, patients were further classified into immune cold, hot and excluded topographies reflecting lymphocyte abundance and localization. The immune topography distribution was further validated with The Cancer Genome Atlas digital image dataset. We showed association between PBRM1 mutation and immune cold topography, STAG1 mutation and immune hot topography and BAP1 mutation and immune excluded topography. With quantitative multiplex immunohistochemistry we analyzed the expression of 23 lymphocyte markers in intratumoral and peritumoral tissue regions. To study spatial interactions, we developed an algorithm quantifying the proportion of adjacent immune cell pairs and their immunophenotypes. Immune excluded tumors were associated with superior overall survival (HR 0.19, p = 0.02) and less extensive metastasis. Intratumoral T cells were characterized with pronounced expression of immunological activation and exhaustion markers such as granzyme B, PD1, and LAG3. Immune cell interaction occurred most frequently in the intratumoral region and correlated with CD45RO expression. Moreover, high proportion of peritumoral CD45RO+ T cells predicted poor overall survival. In summary, intratumoral and peritumoral tissue regions represent distinct immunospatial profiles and are associated with clinicopathologic characteristics.

Distinct exhaustion features of T lymphocytes shape the tumor-immune microenvironment with therapeutic implication in patients with non-small-cell lung cancer

BackgroundReinvigoration of T-cell exhaustion with antibodies has shown promising efficacy in patients with non-small-cell lung cancer (NSCLC). However, the characteristics of T-cell exhaustion with regard to tumor-infiltrating lymphocytes (TILs) are...

Methylglyoxal Levels in Human Colorectal Precancer and Cancer: Analysis of Tumor and Peritumor Tissue.

Colorectal cancer (CRC) is one of the most common cancers worldwide and its incidence is increasing; therefore, an understanding of its oncogenic mechanisms is critical for improving its treatment and management. Methylglyoxal (MGO) has a highly reactive aldehyde group and has been suggested to play a role in oncogenesis. However, no standardized data are currently available on MGO levels in colorectal precancerous and cancerous lesions. We collected 40 matched colorectal tumor and peritumor tissues from patients with low-grade dysplasia (LGD), high-grade dysplasia (HGD), and invasive cancer (IC). MGO levels increased between LGD, HGD, and IC tumor tissues (215.25 ± 39.69, 267.45 ± 100.61, and 587.36 ± 123.19 μg/g protein, respectively; p = 0.014). The MGO levels in peritumor tissue increased and were significantly higher than MGO levels in tumor tissue (197.99 ± 49.40, 738.09 ± 247.87, 933.41 ± 164.83 μg/g protein, respectively; p = 0.002). Tumor tissue MGO levels did not correlate with age, sex, underlying disease, or smoking status. These results suggest that MGO levels fluctuate in progression of CRC and warrants further research into its underlying mechanisms and function in tumor biology.

Alterations of thyroid microbiota across different thyroid microhabitats in patients with thyroid carcinoma

BackgroundIn recent years, the incidence rate of Thyroid carcinoma (TC) has been increasing worldwide. Thus, research on factors of TC carcinogenesis may promote TC prevention and decrease the incidence rate. There are several studies targeting the correlation between gut microbiota and thyroid disease. Carcinogenesis of several malignancies is influenced by microbiota. However, thyroid microbiome of TC has not been revealed. This study investigated thyroid microbiota in different TC microhabitats.MethodsWe performed 16s rRNA gene sequencing using tumor tissues and matched peritumor tissues from 30 patients with TC to characterize thyroid microbiota.ResultsThe richness and diversity of thyroid microbiota were lower in TC tumor samples than in matched peritumor tissues. At the genus level, the core microbiota of thyroid included Sphingomonas, Comamonas, Acinetobacter, Pseudomonas, Microvirgula, and Soonwooa. The abundance of Sphingomonas and Aeromonas was significantly increased in tumor tissues, while the abundance of Comamonas, Acinetobacter, and Peptostreptococcus was significantly enhanced in peritumor tissues. The combination of Comamonas and Sphingomonas could discriminate tumor samples from peritumor samples with an area under the curve (AUC) of 0.981 (95% confidence interval [CI] 0.949–1.000). The abundance of Sphingomonas was significantly higher in N1 stage than in N0 stage. Sphingomonas could distinguish between N0 and N1 stage with an AUC of 0.964 (95% CI 0.907–1.000).ConclusionsThe microbial diversity and composition were significantly different between peritumor and tumor microhabitats from patients with TC, which may eventually affect TC carcinogenesis and progression. The combination of Comamonas and Sphingomonas could serve as a powerful biomarker for discrimination between tumor and peritumor tissues. Furthermore, the higher abundance of Sphingomonas was correlated with lymph node metastasis, indicating that the abundance of Sphingomonas may indicate a poor prognosis for TC patients, and Sphingomonas may play a role in promoting TC progression.

Prognostic significance of imaging features of peritumoral adipose tissue in FDG PET/CT of patients with colorectal cancer

PurposeThis study investigated the relationship of imaging features of primary tumor and peritumoral VAT on PET/CT with histopathological findings of peritumoral VAT and recurrence-free survival (RFS) in patients with colorectal cancer. MethodsWe retrospectively reviewed 133 patients diagnosed with colorectal cancer who underwent staging FDG PET/CT and received curative surgery. Histogram-based imaging features of primary tumor and peritumoral VAT were extracted from PET/CT images. Based on histopathological analysis of peritumoral VAT, the degree of CD4, CD8, and CD163 cell infiltration and the expression of matrix metalloproteinase-11 and interleukin 6 (IL-6) were graded. Differences in imaging parameters based on the histopathological results and the relationships between imaging features and RFS were assessed. ResultsMean CT-attenuation and SUV of peritumoral VAT showed significant positive correlation with CD163 cell infiltration and IL-6 expression of peritumoral VAT. Univariable survival analysis revealed significant correlation between RFS and the mean CT-attenuation, mean SUV, and first-order SUV entropy of peritumoral VAT (p < 0.05). Multivariable analysis indicated that mean SUV and SUV entropy of peritumoral VAT remained significant predictors of RFS after adjustment for age, sex, and T stage (p < 0.05). ConclusionFDG uptake of peritumoral VAT was significantly associated with inflammatory response in peritumoral VAT and was an independent predictor of RFS in colorectal cancer patients.

NIMG-22. PREDICTION OF GLIOBLASTOMA CELLULAR INFILTRATION AND RECURRENCE USING MACHINE LEARNING AND MULTI-PARAMETRIC MRI ANALYSIS: RESULTS FROM THE MULTI-INSTITUTIONAL RESPOND CONSORTIUM

Abstract PURPOSE Multi-parametric MRI and artificial intelligence (AI) methods were previously used to predict peritumoral neoplastic cell infiltration and risk of future recurrence in glioblastoma, in single-institution studies. We hypothesize that important characteristics of peritumoral tissue heterogeneity captured, engineered/selected, and quantified by these methods relate to predictions generalizable in the multi-institutional ReSPOND (Radiomics Signatures for PrecisiON Diagnostics) consortium. METHODS To support further development, generalization, and clinical translation of our proposed method, we trained the AI model on a retrospective cohort of 29 de novo glioblastoma patients from the Hospital of the University of Pennsylvania (UPenn) (Male/Female:20/9, age:22-78 years) followed by evaluation on a prospective multi-institutional cohort of 84 glioblastoma patients (Male/Female:51/33, age:34-89 years) from Case Western Reserve University/University Hospitals (CWRU/UH, 25), New York University (NYU, 13), Ohio State University (OSU, 13), University Hospital Río Hortega (RH, 2), and UPenn (31). Features extracted from pre-resection MRI (T1, T1-Gd, T2, T2-FLAIR, ADC) were used to build our model predicting the spatial pattern of subsequent tumor recurrence. These predictions were evaluated against regions of pathology-confirmed post-resection recurrence. RESULTS Our model predicted the locations that later harbored tumor recurrence with sensitivity 83%, AUC 0.83 (99% CI, 0.73-0.93), and odds ratio 7.23 (99% CI, 7.09-7.37) in the prospective cohort. Odds ratio (99% CI)/AUC(99% CI) per institute were: CWRU/UH, 7.8(7.6-8.1)/0.82(0.75-0.89); NYU, 3.5(3.3-3.6)/0.84(074-0.93); OSU, 7.9(7.6-8.3)/0.8(0.67-0.94); RH, 22.7(20-25.1)/0.94(0.27-1); UPenn, 7.1(6.8-7.3)/0.83(0.76-0.91). CONCLUSION This is the first study that provides relatively extensive multi-institutional validated evidence that AI can provide good predictions of peritumoral neoplastic cell infiltration and future recurrence, by dissecting the MRI signal heterogeneity in peritumoral tissue. Our analyses leveraged the unique dataset of the ReSPOND consortium, which aims to develop and evaluate AI-based biomarkers for individualized prediction and prognostication, by moving from single-institution studies to generalizable, well-validated multi-institutional predictive biomarkers.

IMMU-01. CHARACTERIZATION OF TUMOR-INFILTRATING CD8+ T CELLS IN BRAIN METASTASES

Abstract BACKGROUND Use of immune checkpoint blockade (ICB) therapy has prolonged overall survival in patients with metastatic cancer. One potential strategy to improve the effectiveness of ICB is to target additional inhibitory receptors on exhausted CD8+ T cells, which may promote rescue of CD8+ T cells that do not respond to PD-1 pathway blockade alone. This therapeutic strategy requires knowledge of the inhibitory molecules expressed on tumor-specific CD8+ T cells. Toward achieving this goal, we characterized the phenotype of CD8+ T cells infiltrating brain metastases. METHODS We performed flow cytometry on 45 brain metastases samples, single cell RNA sequencing with T cell receptor (TCR) sequencing on 5 samples, and spatially-resolved transcriptomics on 8 samples. RESULTS Analysis of our scRNA-seq data revealed 4 populations of PD-1+ CD8+ T cells infiltrating brain metastases. One of these populations (cluster A) has a terminal effector exhausted phenotype suggesting that this population contains tumor-specific CD8+ T cells. Two of the other populations (clusters B and C) have a transcriptional profile that suggests they may contain stem-like CD8+ T cells. TCR sequencing shows that cells in cluster A do not express the same TCRs as cells in clusters B and C, suggesting that stem-like cells in clusters B and C are not the progenitors of the terminal effector cells in cluster A. Bystander cells expressing TCRs specific for viral antigens are found predominantly in clusters B and C, further supporting the hypothesis that cluster A contains tumor-specific cells. Spatial transcriptomics reveals that cluster A cells are infiltrating the tumor parenchyma while cluster B and C cells are predominantly in peri-tumoral inflammatory tissue. CONCLUSIONS Brain metastases are infiltrated by a population of terminally-differentiated effector CD8+ T cells which express co-inhibitory molecules that may be potential therapeutic targets to improve control of metastatic disease in the brain.

BRMP-04. AI-based biomarker of the peritumoral region using tissue microstructure

Abstract PURPOSE Glioblastomas, the most common malignant brain tumor [BS1], infiltrate into peritumoral brain structures, making clinical management challenging. An unmet need is to develop a biomarker that reliably characterize infiltration in the peritumoral region, where surgical biopsy or resection may be hazardous. Diffusion tensor imaging (DTI) with multicompartment modeling can characterize extracellular free water, providing unique information of the tissue microstructure that is able to capture this heterogeneity. We propose a novel biomarker based on peritumoral tissue microstructure, using deep-learning on DTI-based free water map. METHOD Peritumoral regions were automatically segmented for 136 patients with brain tumors (86 glioblastomas and 50 metastases, ages 23–87 years, 65 females). We trained a Convolutional Neural Network (CNN) on free-water maps using automatically defined patches in the peritumoral area from glioblastomas and metastases, labeled as low free-water and high free-water to extract a microstructural index for each voxel. To extract the biomarker, we grouped peritumoral voxels into connected components (CCs) where adjacent voxels have high (&amp;gt;0.9) microstructural index values. Two independent test sets related to two clinically significant problems were evaluated: i) metastases vs. glioblastomas; ii) glioma patients categorized into short and long survival groups and the number of CCs were statistically compared. RESULT Two-sample t-tests showed significant group difference in the number of CCs between metastases and glioblastomas (p&amp;lt; 0.05), and short and long-survivals (p&amp;lt;0.05) with higher number of CCs in metastases and long-survivals, which suggests smaller number of voxels in CCs. CONCLUSION The proposed biomarker based on CCs of microstructural index captures the differences in infiltration of the peritumoral region, showing larger CCs in glioblastomas and short-survivals corresponding to higher infiltration. CLINICAL IMPORTANCE The proposed biomarker provides a novel insight into the peritumoral microenvironment and can be derived from clinically feasible DTI data, providing new possibilities for the diagnosis and treatment of glioblastoma.

Protective or Risk Factors for Postoperative Pancreatic Fistulas in Malignant Pathology.

Introduction: Malignant tumors are associated with a low incidence of postoperative pancreatic fistulas. The presence of peritumoral fibrosis is considered the protective factor for the development of postoperative pancreatic fistulas after pancreatic resections for pancreatic ductal adenocarcinomas. Methods: We analyzed a series of 109 consecutive patients with pancreatic resections for malignant pathology: pancreatic ductal adenocarcinomas and periampullary adenocarcinomas. The incidence of postoperative pancreatic fistulas has been reported in tumor histological type, in the presence of peritumoral fibrosis, and in the association between adenocarcinomas and areas of acute pancreatitis. The data obtained were processed with the statistical analysis program SPSS, and statistically significant p were considered at a value <0.05. Results: For the entire study group, the incidence of postoperative pancreatic fistulas was 11.01%. The lowest incidence was observed in the group of patients with pancreatic ductal adenocarcinomas (4.06% vs. 25.72% in the group with periampullary adenocarcinoma), with a p = 0.002. The presence of peritumoral fibrous tissue was observed in 49.31% of cases without pancreatic fistulas, and in 54.54% of cases that developed this postoperative complication (p = 0.5). Also, the peritumoral fibrous tissue had a uniform distribution depending on the main diagnosis (56.14% in pancreatic ductal adenocarcinoma group vs. 37.04% in periampullary adenocarcinoma group, with a p = 0.08). In the group of patients who associated areas of acute pancreatitis on the resections, the incidence of postoperative pancreatic fistulas was 7.8 times higher (30% vs. 3.8%, p = 0.026). Conclusions: Peritumoral fibrous tissue was not a factor involved in the developing of postoperative pancreatic fistulas. The association of adenocarciomas with areas of acute pancreatitis has led to a significant increase in postoperative pancreatic fistulas, which is a significant and independent risk factor.

Long-Term Characterization of MRI-Morphologic Alterations After Active Motion-Compensated Liver SBRT

<h3>Purpose/Objective(s)</h3> To characterize the post-SBRT MRI-morphologic alterations in long-term survivors with MRI-based follow-up (FU) in patients treated by actively motion managed gantry-based and robotic liver SBRT. <h3>Materials/Methods</h3> Patients treated with gantry-based (with breath-hold-gating and ultrasound tracking) or robotic-based SBRT (with real-time fiducial tracking) who had long-term follow-up (FU, ≥ 90 days) were evaluated. Post-SBRT MRI-evidenced morphologic alterations (MMAs) were contoured manually on each T1-weighted contrast-enhanced. Volumetric data and liver volume were documented at each FU. Change's dynamics and significance was assessed for each time point. <h3>Results</h3> The median follow-up was 12.5 months [0.5 - 84]. Seventy PTVs from 62 patients were assessable. After 3 - 6 months, 95.7% (<b>n =</b> 67) of treated lesions developed MMAs with a median volume of 122.44 cc [8.17 – 699.34]. Characterization included 48 (71.6%) hypointense and 19 (28.4%) hyperintense MMAs. Twenty-one (31.3%) MMAs completely resolved after median 12 months [6 – 36] post-SBRT. At the last follow-up, 68.7% were still present (6 – 84 months). Thirty-seven (55.2%) MMAs did not resolve completely and reduced in volume with longer FU. Since the 3-month control baseline, a significant volume reduction to a median of 43.3% after 6 months (<i>P</i> < 0.001), 31% after 9 months (<i>P</i> = 0.022) and 13% after 12 – 24 months (<i>P</i> = 0.041), was observed. Liver volumes reduced to a mean 95.1% from the baseline at 3 months (<i>P</i> = 0.001) and remained afterwards unmodified. <h3>Conclusion</h3> Post-radiogenic MRI-morphologic alterations in peritumoral healthy liver tissue either completely resolve or significantly reduce in volume along the first 2 years after treatment. Clinical correlation should be further investigated.

High frequency oscillations associate with neuroinflammation in low-grade epilepsy associated tumors

ObjectiveHigh frequency oscillations (HFOs) in intraoperative electrocorticography (ioECoG) are thought to be generated by hyperexcitable neurons. Inflammation may promote neuronal hyperexcitability. We investigated the relation between HFOs and inflammation in tumor-related epilepsy. MethodsWe identified HFOs (ripples 80–250 Hz, fast ripples 250–500 Hz) in the preresection ioECoG of 32 patients with low-grade tumors. Localization of recorded HFOs was classified based on magnetic resonance imaging reconstructions: in tumor, in resected non-tumorous area and outside the resected area. We tested if the following inflammatory markers in the tumor or peritumoral tissue were related to HFOs: activated microglia, cluster of differentiation 3 (CD3)-positive T-cells, interleukin 1-beta (IL1β), toll-like receptor 4 (TLR4) and high mobility group box 1 protein (HMGB1). ResultsTumors that generated ripples were infiltrated by more CD3-positive cells than tumors without ripples. Ripple rate outside the resected area was positively correlated with IL1β/TLR4/HMGB1 pathway activity in peritumoral area. These two areas did not directly overlap. ConclusionsRipple rates may be associated with inflammatory processes. SignificanceOur findings support that ripple generation and spread might be associated with synchronized fast firing of hyperexcitable neurons due to certain inflammatory processes. This pilot study provides arguments for further investigations in HFOs and inflammation.

The prognostic value of intratumoral and peritumoral tumor-infiltrating FoxP3+Treg cells in of pancreatic adenocarcinoma: a meta-analysis

BackgroundTumor-infiltrating lymphocytes (TILs) are major participants in the tumor microenvironment. The prognostic value of TILs in patients with pancreatic cancer is still controversial.MethodsThe aim of our meta-analysis was to determine the impact of FoxP3+Treg cells on the survival of pancreatic cancer patients. We searched for related studies in PubMed, EMBASE, Ovid, and Cochrane Library from the time the databases were established to Mar 30, 2017. We identified studies reporting the prognostic value of FoxP3+Treg cells in patients with pancreatic cancer. Overall survival (OS) and disease-free survival (DFS)/progression-free survival (PFS)/relapse-free survival (RFS) were investigated by pooling the data. The pooled hazard ratios (HRs) with 95% confidence intervals (95% CI) were used to evaluate the association between FoxP3+Treg cells and survival outcomes of pancreatic cancer patients. A total of 972 pancreatic cancer patients from 8 studies were included in our meta-analysis.ResultsHigh levels of infiltration with FoxP3+Treg cells were significantly associated with poor OS (HR=2.13; 95% CI 1.64–2.77; P<0.05) and poor DFS/PFS/RFS (HR=1.70; 95% CI 1.04 ~ 2.78; P< 0.05). Similar results were also observed in the peritumoral tissue; high levels of FoxP3+Treg cells were associated with poor OS (HR =2.1795% CI, CI 1.50–3.13).ConclusionThis meta-analysis indicated that high levels of intratumoral or peritumoral FoxP3+Treg cell infiltration could be recognized as a negative factor in the prognosis of pancreatic cancer.

Clinical Significance of Peritumoral Adipose Tissue PET/CT Imaging Features for Predicting Axillary Lymph Node Metastasis in Patients with Breast Cancer.

We investigated whether textural parameters of peritumoral breast adipose tissue (AT) based on F-18 fluorodeoxyglucose (FDG) PET/CT could predict axillary lymph node metastasis in patients with breast cancer. A total of 326 breast cancer patients with preoperative FDG PET/CT were retrospectively enrolled. PET/CT images were visually assessed and the maximum FDG uptake of axillary lymph nodes (LN SUVmax) was measured. From peritumoral breast AT, 38 textural features of PET imaging were extracted. The diagnostic ability of PET based on visual analysis, LN SUVmax, and textural features of peritumoral breast AT for predicting axillary lymph node metastasis were assessed using the area under the receiver operating characteristic curve (AUC) values. Among the 38 peritumoral breast AT textural features, grey-level co-occurrence matrix (GLCM) entropy showed the highest AUC value (0.830) for predicting axillary lymph node metastasis. The value of GLCM entropy was higher than that of visual analysis (0.739; p < 0.05) and the AUC value was comparable to that of LN SUVmax (0.793; p > 0.05). In the subgroup analysis of patients with negative findings on visual analysis, GLCM entropy still showed a high diagnostic ability (AUC: 0.759) in predicting lymph node metastasis. The findings suggest a potential diagnostic role of PET/CT imaging features of peritumoral breast AT in predicting axillary lymph node metastasis in patients with breast cancer.

Long-Wave Infrared Imaging for Intraoperative Cancer Detection-What is the True Temperature of a Cancer?

During cancer operations, the cancer itself is often hard to delineate-buried beneath healthy tissue and lacking discernable differences from the surrounding healthy organ. Long-wave infrared, or thermal, imaging poses a unique solution to this problem, allowing for the real-time label-free visualization of temperature deviations within the depth of tissues. The current study evaluated this technology for intraoperative cancer detection. In this diagnostic study, patients with gastrointestinal, hepatobiliary, and renal cancers underwent long-wave infrared imaging of the malignancy during routine operations. It was found that 74% were clearly identifiable as hypothermic anomalies. The average temperature difference was 2.4°C (range 0.7 to 5.0) relative to the surrounding tissue. Cancers as deep as 3.3cm from the surgical surface were visualized. Yet, 79% of the images had clinically relevant false positive signals [median 3 per image (range 0 to 10)] establishing an accuracy of 47%. Analysis suggests that the degree of temperature difference was primarily determined by features within the cancer and not peritumoral changes in the surrounding tissue. These findings provide important information on the unexpected hypothermal properties of intra-abdominal cancers, directions for future use of intraoperative long-wave infrared imaging, and new knowledge about the in vivo thermal energy expenditure of cancers and peritumoral tissue.

Quantitative analysis of near infrared optical signal in fluorescence molecular navigation surgery for oral squamous cell carcinoma

Objective: To evaluate the effect of quantitative analysis of optical signal in the near infrared fluorescence molecular navigation surgery for oral squamous cell carcinoma (OSCC). Methods: SCC9, HSC3 and epithelial cell lines (Leuk-1) were co-cultured with indocyanine green (ICG) for 6 hours in vitro in order to verify whether the quantitative analysis of near infrared optical signal could distinguish tumor cells from normal cells. A total of 16 BALB/c male mice (5-6 weeks, 20-25 g) were selected and fed in clean grade equipment and were equally divided into two groups. SCC9 and HSC3 cells were inoculated into the back of each mouse at a concentration of 1×106 cells/ml to establish a subcutaneous graft tumor model. The 5 mg/kg ICG was injected into the caudal vein to each of the tumor bearing mouse and the difference between OSCC and normal tissues was then analyzed by near infrared optical signal quantitative analysis (Paired t test). Ten patients with OSCC were enrolled in the Department of Stomatology of the First Affiliated Hospital of Bengbu Medical College from November 2019 to July 2020, including 6 patients with tongue squamous cell carcinoma and 4 patients with buccal squamous cell carcinoma.The patients were 6 males and 4 females and the range of age was from 46 to 71 years with an average age of 58.6 years. These patients were injected ICG (0.75 mg/kg) via the cubital vein at 6-8 h before surgery. Intraoperatively, the fluorescence intensities (FI) of near infrared signal were measured at tumor, peritumor tissues (2.0 cm beyond the tumor boundary) and normal tongue or buccal mucosa respectively. The signal background ratios (SBR) from the three site groups were assessed using one-way ANOVA followed by the Tukey post hoc test for multiple comparisons. Results: In vitro, the levels of near infrared FI in HSC3 and SCC9 groups were higher than that in Leuk-1group (P<0.01). In vivo, the result showed that the SBR of OSCC and normal tissues was 8.67±0.35. Clinical studies showed that the intensity of tumor [(408.23±101.51) arbitrary units (AU)] was significantly higher than those of peritumoral [(253.12±64.89) AU] and normal tissues [(261.50±80.47) AU] respectively. The SBRs of near infrared FI of tumor and peritumoral tissues, tumor and normal tissues were 1.61±0.53 and 1.56±0.48 respectively, while that of peritumoral and normal tissues was 0.96±0.17. Conclusions: The quantitative analysis of near infrared optical signal could distinguish OSCC from normal cells and could locate the OSCC tissue intraoperatively. Optical signal quantification and ICG near infrared fluorescence molecular technology possessed the feasibility in primary OSCC resection.

The Potential Role of Peritumoral Apparent Diffusion Coefficient Evaluation in Differentiating Glioblastoma and Solitary Metastatic Lesions of the Brain.

Differentiating glioblastoma (GBM) and solitary metastasis is not always possible using conventional magnetic resonance imaging (MRI) techniques. In conventional brain MRI, GBM and brain metastases are lesions with mostly similar imaging findings. In this study, we investigated whether apparent diffusion coefficient (ADC) ratios, ADC gradients, and minimum ADC values in the peritumoral edema tissue can be used to discriminate between these two tumors. This retrospective study was approved by the local institutional review board with a waiver of written informed consent. Prior to surgical and medical treatment, conventional brain MRI and diffusion-weighted MRI (b = 0 and b = 1000) images were taken from 43 patients (12 GBM and 31 solitary metastasis cases). Quantitative ADC measurements were performed on the peritumoral tissue from the nearest segment to the tumor (ADC1), the middle segment (ADC2), and the most distant segment (ADC3). The ratios of these three values were determined proportionally to calculate the peritumoral ADC ratios. In addition, these three values were subtracted from each other to obtain the peritumoral ADC gradients. Lastly, the minimum peritumoral and tumoral ADC values, and the quantitative ADC values from the normal-appearing ipsilateral white matter, contralateral white matter, and ADC values from cerebrospinal fluid (CSF) were recorded. For the differentiation of GBM and solitary metastasis, ADC3 / ADC1 was the most powerful parameter with a sensitivity of 91.7% and specificity of 87.1% at the cut-off value of 1.105 (p < 0.001), followed by ADC3 / ADC2 with a cut-off value of 1.025 (p = 0.001), sensitivity of 91.7%, and specificity of 74.2%. The cut-off, sensitivity and specificity of ADC2 / ADC1 were 1.055 (p = 0.002), 83.3%, and 67.7%, respectively. For ADC3 - ADC1, the cut-off value, sensitivity, and specificity were calculated as 150 (p < 0.001), 91.7%, and 83.9%, respectively. ADC3 - ADC2 had a cutoff value of 55 (p = 0.001), sensitivity of 91.7%, and specificity of 77.4, whereas ADC2 - ADC1 had a cut-off value of 75 (p = 0.003), sensitivity of 91.7%, and specificity of 61.3%. Among the remaining parameters, only the ADC3 value successfully differentiated between GBM and metastasis (GBM 1802.50 ± 189.74 vs. metastasis 1634.52 ± 212.65, p = 0.022). The integration of the evaluation of peritumoral ADC ratio and ADC gradient into conventional MR imaging may provide valuable information for differentiating GBM from solitary metastatic lesions.

Oncostatin M promotes hepatic progenitor cell activation and hepatocarcinogenesis via macrophage-derived tumor necrosis factor-α

Hepatocellular carcinoma (HCC) usually occurs at the late stage of chronic liver injury. Oncostatin M (OSM) is a tumor-associated cytokine highly expressed in cirrhosis and HCC patients; however, its role in hepatocarcinogenesis has not been clearly elucidated. In this study, we investigated the effect of OSM on HCC occurrence in a rat model of N-diethylnitrosamine-induced HCC. OSM overexpression significantly increased the number of tumor nodules and shortened the overall survival of the rats. Notably, OSM promoted HPC activation in vivo but did not directly regulate the proliferation of the HPC cell line in vitro. Further, OSM induced tumor necrosis factor-α (TNF-α) secretion and CD68+ macrophage accumulation, which were positively correlated with HPC activation. Additionally, TNF-α or macrophage depletion inhibited the promoting effect of OSM on hepatocarcinogenesis and HPC activation. Furthermore, OSM expression in the peritumoral tissues of HCC was positively correlated with poor overall survival of patients. In conclusion, OSM plays an important role in hepatocarcinogenesis by regulating the liver inflammation environment. Hence, OSM could be used as a potential target for HCC prevention and therapy or as an indicator of HCC prognosis.

Oral microbiota affects the efficacy and prognosis of radiotherapy for colorectal cancer in mouse models.

Radiotherapy is inevitably intertwined with various side effects impairing the quality of life of cancer patients. Here, we report the possibility that alterations of the oral microbiota influence the therapeutic efficacy and prognosis of radiotherapy for primary rectal cancer and colorectal cancer (CRC) liver metastases that pathologically disrupt gastrointestinal integrity and function. 16S rRNA sequencing shows that oral microbiota alterations change the gut bacterial composition within tumors but not in adjacent peritumor tissues in CRC mouse models. Specifically, buccal Fusobacterium nucleatum migrates to the CRC locus and impairs the therapeutic efficacy and prognosis of radiotherapy. Administration of a specific antibiotic, metronidazole, abrogates the adverse effects of oral microbiome fluctuation on radiotherapy for CRC. The oral microbiota were also associated with radiation-induced intestinal injury via intestinal microbes. Our findings demonstrate that the oral microbiome in synergy with its intestinal counterparts impinges on the efficacy and prognosis of radiotherapy for CRC.