Biomarkers For Cancer Prediction Research Articles

Abstract PO5-06-08: Real-world analysis of efficacy, adverse events and predictive biomarkers for advanced triple negative breast cancer (TNBC) treated with immune check point Inhibitors (ICI): A single center experience

Abstract Introduction KEYNOTE-355 investigated the addition of pembrolizumab to chemotherapy in advanced TNBC patients (pts) with PD-L1 positive tumors showing median overall survival (OS) of 23.0 months (mos) and median progression-free survival (PFS) of 16.1 mos. Given significant OS benefit with pembrolizumab, it is the current standard of care while the indication of atezolizumab has been withdrawn due to lack of OS benefit in IMPASSION-130. Clinical efficacy and adverse events in pts on this treatment regimen in clinical practice is unknown and understanding the real-world outcomes of this regimen is critical. Methods We conducted a retrospective, single-center observational study among TNBC pts treated with ICI (Pembrolizumab or Atezolizumab) at Roswell Park Comprehensive Cancer Center from January 2017 to May 2023. Demographics and clinicopathological variables were collected including comorbidities, laboratory data, sites of metastases (mets), treatment received, immune related adverse events (irAEs), and clinical outcomes. Adverse events were reported using the Common Terminology Criteria for Adverse Events v5.0. Serial CT scans were reviewed and response rate was determined using RECIST v1.1. Patient demographic, clinical and outcome characteristics were summarized by treatment and survival outcomes were obtained using standard Kaplan-Meier methods. Associations between survival outcomes and baseline or treatment characteristics were evaluated using Cox regression models using Firth’s method. All analyses were conducted in SAS v9.4 at a significance level of 0.05. Results A total of 44 pts with advanced TNBC treated with ICI were included (23 received pembrolizumab and 21 received Atezolizumab). The study population consisted of all female pts with stage IV disease, median age 53.7 years (IQR 30.4-85.2), 68.2 % (30/44) White, 25.0% (11/44) Black, 34.1% (15/44) obese (BMI≥30). 27.3% (12/44) pts developed any grade irAEs which included myocarditis (4.5%), rash (9.1%), hyperthyroidism (6.8%), hypothyroidism (4.5%), adrenal insufficiency (2.3%), diabetes mellitus (2.4%), colitis (2.3%), and transaminitis (2.3%). Distribution of reported irAE was 25% grade 1 (3/12), 66.7% grade 2 (8/12) and 8.3% grade 3 (1/12). 75% pts (33/44) received standard treatment (ICI+ chemotherapy) of which 72.7 % (24/33) received it in the first-line setting. Median OS in pts treated in first line was 16.2 mos (95% CI, 10.7-NR) and median PFS was 4.4 mos (95% CI, 2.7-8.4). Overall response rate (ORR) was 29.1% (7/24) of which 8.3% (2/24) had complete response and 20.8% (5/24) had partial response. ORR was 22.2 % (2/9) in pembrolizumab cohort and 33.3 % (5/15) in atezolizumab cohort. Among pts with first line treatment, obese pts were found to have improved PFS compared to non-obese (11.5 vs 3.8 mos, univariate hazard ratio (HR) 0.46, 95% CI 0.23-0.93, p= 0.031), and this difference was maintained in multivariable analysis even after adjusting for age (adjusted HR (aHR) 0.40, 95% CI 0.17-0.98, p= 0.044). Pts with brain mets had poor extracranial PFS compared to those without brain mets (2.8 vs. 5.2 mos, HR 2.25, 95% CI 1.08-4.68, p= 0.036), however this difference was not observed when further adjusted for age (aHR 2.27, 95% CI= 0.91-5.68, p= 0.08). Conclusion Clinical outcomes in our study were inferior to KEYNOTE-355 where median PFS was 16.1 mos and OS was 23.0 mos and ORR was 52.7% for PD-L1 positive population. This may reflect a more heterogeneous population of pts treated in routine clinical practice who are typically less fit than pts on clinical trials. Our study found improved outcomes among obese patients, similar to data reported in other disease settings. These data warrant multi-center validation with larger number of patients. Citation Format: Archit Patel, Arya Mariam Roy, Malak Alharbi, Kristopher Attwood, Chi-Chen Hong, Song Yao, Thaer Khoury, Amy Early, Tracey O'Connor, Ellis Levine, Shipra Gandhi. Real-world analysis of efficacy, adverse events and predictive biomarkers for advanced triple negative breast cancer (TNBC) treated with immune check point Inhibitors (ICI): A single center experience [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 PO5-06-08.

Contribution of tumour and immune cells to PD-L1 expression as a predictive biomarker in metastatic triple-negative breast cancer: exploratory analysis from KEYNOTE-119.

The efficacy of pembrolizumab monotherapy versus chemotherapy increased with increasing programmed death ligand 1 (PD-L1) expression, as quantified by combined positive score (CPS; PD-L1 expression on both tumour cells and immune cells) in patients with previously treated metastatic triple-negative breast cancer (mTNBC) in the phase 3 KEYNOTE-119 study. This exploratory analysis was conducted to determine whether the expression of PD-L1 on tumour cells contributes to the predictive value of PD-L1 CPS in mTNBC. PD-L1 expression in tumour samples was assessed using PD-L1 IHC 22C3 pharmDx and quantified using both CPS and tumour proportion score (TPS; PD-L1 expression on tumour cells alone). Calculated immune cell density (CID) was defined as CPS minus TPS. The ability of each scoring method (CPS, TPS, and CID) to predict clinical outcomes with pembrolizumab was evaluated. With pembrolizumab, the area under the receiver operating characteristic curve was 0.69 (95% CI = 0.58-0.80) for CPS, 0.55 (95% CI = 0.46-0.64) for TPS, and 0.67 (95% CI = 0.56-0.77) for CID. After correction for cutoff prevalence, CPS performed as well as, if not better than, CID with respect to predicting objective response rate, progression-free survival, and overall survival. Data from this exploratory analysis suggest that, although PD-L1 expression on immune cells alone is predictive of response to programmed death 1 blockade in mTNBC, adding tumour PD-L1 expression assessment (i.e. CPS, which combines immune cell and tumour cell PD-L1 expression) may improve prediction. PD-L1 CPS thus remains an effective and broadly applicable uniform scoring system for enriching response to programmed death 1 blockade with pembrolizumab in mTNBC as well as other tumour types.

Spatial distribution of tumor‐resident macrophages as predictive biomarkers in endometrial cancer

Spatial distribution of tumor‐resident macrophages as predictive biomarkers in endometrial cancer

Predictive Value and Immunological Role of the HSPA5 Gene in Cervical Cancer.

Cervical cancer (CC) ranks fourth among women's malignancies worldwide and seriously affects women's health. HSPA5 is a heat shock protein, also known as glucose regulatory protein 78 (GRP78). Upregulation of HSPA5 has been reported to be closely associated with multiple types of tumors. However, the specific role of HSPA5 in cervical cancer has not been discovered. In our study, we explored the prognostic value of HSPA5 in CC. Here, we analyzed the (TCGA) and (UCSC) databases, the analysis of HSPA5 in many tumors types was conducted with the "wilcox. test" method. A False Discovery Rate (FDR) value < 0.05 and Log2 | (fold change, FC) |> 1 were set as the cutoffs. "*", "**", and "***" indicate FDR < 0.05, < 0.01, and < 0.001, respectively, and further used human cervical cancer cells for q-PCR and western blotting detection. q-PCR and western blotting results showed that HSPA5 was highly expressed in cervical cancer cells, while it was expressed at low levels in normal cells (P < 0.05).We also analyzed the immunohistochemical data. immunohistochemical analysis results showed that HSPA5 was highly expressed in human cervical cancer, while it was expressed at low levels in normal tissues (P < 0.05). Analysis in TCGA-UCSC showed that the proportion of G3 in the group with high expression of HSPA5 was relatively high (P < 0.05). Enrichment analysis and survival analysis showed that the increased expression of HSPA5 in cervical cancer was related to the survival of CC and was involved in the regulation of biological behavior and molecular signaling pathways of cervical cancer. The correlation analysis of immune checkpoint and immune infiltration showed that HSPA5 was involved in the regulation of immune process of cervical cancer (P < 0.05). Drug sensitivity correlation analysis showed that HSPA5 was a sensitive target for tumor drugs (P < 0.05). In brief, those results suggest that HSPA5 can act as an oncogene of CC development and can serve as an effective predictive biomarker in cervical cancer.

Emerging measurements for tumor-infiltrating lymphocytes in breast cancer.

Tumor-infiltrating lymphocytes are a general term for lymphocytes or immune cells infiltrating the tumor microenvironment. Numerous studies have demonstrated tumor-infiltrating lymphocytes to be robust prognostic and predictive biomarkers in breast cancer. Recently, immune checkpoint inhibitors, which directly target tumor-infiltrating lymphocytes, have become part of standard of care treatment for triple-negative breast cancer. Surprisingly, tumor-infiltrating lymphocytes quantified by conventional methods do not predict response to immune checkpoint inhibitors, which highlights the heterogeneity of tumor-infiltrating lymphocytes and the complexity of the immune network in the tumor microenvironment. Tumor-infiltrating lymphocytes are composed of diverse immune cell populations, including cytotoxic CD8-positive T lymphocytes, B cells and myeloid cells. Traditionally, tumor-infiltrating lymphocytes in tumor stroma have been evaluated by histology. However, the standardization of this approach is limited, necessitating the use of various novel technologies to elucidate the heterogeneity in the tumor microenvironment. This review outlines the evaluation methods for tumor-infiltrating lymphocytes from conventional pathological approaches that evaluate intratumoral and stromal tumor-infiltrating lymphocytes such as immunohistochemistry, to the more recent advancements in computer tissue imaging using artificial intelligence, flow cytometry sorting and multi-omics analyses using high-throughput assays to estimate tumor-infiltrating lymphocytes from bulk tumor using immune signatures or deconvolution tools. We also discuss higher resolution technologies that enable the analysis of tumor-infiltrating lymphocytes heterogeneity such as single-cell analysis and spatial transcriptomics. As we approach the era of personalized medicine, it is important for clinicians to understand these technologies.

Abstract 1304: Employing widening funds to address inequity in cancer research - example of the STEPUPIORS collaborative rectal cancer project

Abstract Introduction: Treatment of locally advanced rectal cancer (LARC) using neoadjuvant chemoradiotherapy (nCRT) improves local control and survival, but response varies. Patients treated at the Institute for Oncology and Radiology of Serbia (IORS) who undergo surgery upon complete response might be exposed to risks and poor quality of life. A consortium dedicated to redefining prognostic and predictive biomarkers in rectal cancer was formed within the framework of the STEPUPIORS Horizon Europe project. The current study evaluated whether employing collaborative widening funds might lead to sustainable strategies for cancer treatment, lowering inequity and steering societal impact, especially in countries with limited resources, using a pilot rectal cancer project. Patients and Methods: The analysis was performed in the period Oct 01, 2022, to Oct 01, 2023, with a Serbian coordinating institution and partners from Spain, Greece, and the Netherlands as expert twinning centers. RT was administered to 75 patients with LARC using volumetric modulated arc therapy-simultaneous integrated boost approach/concomitant chemotherapy (5FU/Leucovorin, week 1&amp;5) for the first time in Serbia. A comprehensive approach towards building human capacities on biobanking, multiomics analyses and project management was developed through intensive training and expert visits. Consensus consortium decisions were reached on regular partner meetings. Results: Patients with clinical complete response (16.0%) and initially distant-located tumors were enrolled in the watch and wait approach and are under follow up. Developed pipelines for multiomics analyses led to 4 high-quality papers on new predictive biomarkers to nCRT in LARC and the deposition of omics data in open-science repositories following FAIR data principles. A first Serbian cancer biobank was successfully installed. Fifteen IORS researchers (87% female), were certified in biobanking. A grant management office was established to provide and support the sustainability of future research projects. This led to 5 new grant applications and enrollment of 1 female project member in a Masters program for Management in the Health Care System. Conclusion: This study showed that even within the first 12 months, implementation of a 3-year collaborative grant dedicated to a specific research problem, might significantly change educational and treatment strategies enabling better patient care (OCEBM level of evidence 3). The results highlight that disparities in cancer outcomes and health equity might only be addressed by progressing beyond descriptions of said outcomes and taking specific action. Systematic, long-term strategic initiatives and collaborations among relevant stakeholders and ethical, legal and societal structures are needed in more countries. Acknowledgements: Horizon Europe Project STEPUPIORS (101079217). Citation Format: Milena Cavic, Ana Djuric, Mladen Marinkovic, Aleksandra Stanojevic, Miljana Tanic, Snezana Bjelogrlic, Jelena Spasic, Ana Damjanovic, Marija Djordjic Crnogorac, Ana Vuletic, Katarina Mirjacic Martinovic, Marko Radulovic, Suzana Stojanovic-Rundic, Ana Krivokuca, Radmila Jankovic, Sergi Castellvi-Bel, Jerome Zoidakis, Remond J. Fijneman. Employing widening funds to address inequity in cancer research - example of the STEPUPIORS collaborative rectal cancer project [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 1304.

Withdrawal: Urinary exosomal tRNA-derived small RNA signatures as a predictive biomarker in lung cancer.

Withdrawal: Urinary exosomal tRNA-derived small RNA signatures as a predictive biomarker in lung cancer, published in FEBS OPEN BIO, 10.1002/2211-5463.13716. The above article, published online on 9th October 2023 in Wiley Online Library (wileyonlinelibrary.com), has been withdrawn by agreement between the journal Editor in Chief, Miguel De la Rosa, and Wiley Periodicals LLC. The withdrawal has been agreed following no response from the author to requests to sign the Journal's publishing license/to requests to approve their article proof for publication. https://doi.org/10.1002/2211-5463.13716.

Searching for the "Holy Grail" of breast cancer recurrence risk: a narrative review of the hunt for a better biomarker and the promise of circulating tumor DNA (ctDNA).

This paper is a narrative review of a major clinical challenge at the heart of breast cancer care: determining which patients are at risk of recurrence, which require systemic therapy, and which remain at risk in the survivorship phase of care despite initial therapy. We review the literature on prognostic and predictive biomarkers in breast cancer with a focus on detection of minimal residual disease. While we have many tools to estimate and refine risk that are used to individualize local and systemic therapy, we know that we continue to over treat many patients and undertreat others. Many patients also experience what is, at least in hindsight, needless fear of recurrence. In this review, we frame this dilemma for the practicing breast oncologist and discuss the search for what we term the "holy grail" of breast cancer evaluation: the ideal biomarker of residual distant disease. We review the history of attempts to address this problem and the up-to-date science on biomarkers, circulating tumor cells and circulating tumor DNA (ctDNA). This review suggests that the emerging promise of ctDNA may help resolve a crticical dilemma at the heart of breast cancer care, and improve prognostication, treatment selection, and outcomes for patients with breast cancer.

Current and Emerging Diagnostic, Prognostic, and Predictive Biomarkers in Head and Neck Cancer.

Head and neck cancers (HNC) are a biologically diverse set of cancers that are responsible for over 660,000 new diagnoses each year. Current therapies for HNC require a comprehensive, multimodal approach encompassing resection, radiation therapy, and systemic therapy. With an increased understanding of the mechanisms behind HNC, there has been growing interest in more accurate prognostic indicators of disease, effective post-treatment surveillance, and individualized treatments. This chapter will highlight the commonly used and studied biomarkers in head and neck squamous cell carcinoma.

Cancer-associated fibroblasts (CAFs) based model reveals potential for predicting bladder cancer patients’ prognoses and immunotherapy responses

Aim: The purpose of this study is to enhance the understanding of bladder cancer and the role of cancer-associated fibroblasts (CAFs) in its progression. We aim to identify CAF-specific biomarkers and develop a prognostic prediction model based on CAFs, thereby contributing to the advancement of treatment strategies and the identification of prognostic and predictive biomarkers for bladder cancer. Method: We employed single-cell RNA sequencing to detect biomarkers for CAFs in bladder cancer cells. Bladder cancer cohorts were categorized into low- and high-CAF groups using the ssGSEA algorithm. The study also explored the association between CAF-related scores, immune-related cells, and immune checkpoint-related genes. Furthermore, we performed GSVA analysis to understand the biological features of CAFs and their link to various cancer-related pathways. Result: Ten genes were identified as CAF markers in bladder cancer cells. A significant difference was found with 2712 differentially expressed genes between low-CAF and high-CAF tissues. The CAFs-based prognostic prediction model included nine genes (ALDH1L2, AL450384.2, EMP1, LINC02362, WFIKKN1, GOLGA8A, POU5F1, AL354919.2, PTPRR), which are potentially crucial in predicting bladder cancer prognosis. The GSVA analysis revealed the involvement of several cancer-related pathways, such as WNT, toll-like receptor, TGF-beta, MAPK, and MTOR signaling pathways, in the CAFs-based prognostic model. Conclusion: This study highlights the significant role of CAFs in the progression and prognosis of bladder cancer. The identified CAF biomarkers and the constructed prognostic model provide valuable insights for future research and potential therapeutic targets. CAF-dependent pathways are promising for the development of new treatments and improving the prognosis of bladder cancer patients.

Mismatch Repair Deficiency as a Predictive and Prognostic Biomarker in Endometrial Cancer: A Review on Immunohistochemistry Staining Patterns and Clinical Implications.

Among the four endometrial cancer (EC) TCGA molecular groups, the MSI/hypermutated group represents an important percentage of tumors (30%), including different histotypes, and generally confers an intermediate prognosis for affected women, also providing new immunotherapeutic strategies. Immunohistochemistry for MMR proteins (MLH1, MSH2, MSH6 and PMS2) has become the optimal diagnostic MSI surrogate worldwide. This review aims to provide state-of-the-art knowledge on MMR deficiency/MSI in EC and to clarify the pathological assessment, interpretation pitfalls and reporting of MMR status.

Liquid Biopsy: An Emerging Diagnostic, Prognostic, and Predictive Tool in Gastric Cancer.

Liquid biopsy, a minimally invasive procedure that causes minimal pain and complication risks to patients, has been extensively studied for cancer diagnosis and treatment. Moreover, it facilitates comprehensive quantification and serial assessment of the whole-body tumor burden. Several biosources obtained through liquid biopsy have been studied as important biomarkers for establishing early diagnosis, monitoring minimal residual disease, and predicting the prognosis and response to treatment in patients with cancer. Although the clinical application of liquid biopsy in gastric cancer is not as robust as that in other cancers, biomarker studies using liquid biopsy are being actively conducted in patients with gastric cancer. Herein, we aimed to review the role of various biosources that can be obtained from patients with gastric cancer through liquid biopsies, such as blood, saliva, gastric juice, urine, stool, peritoneal lavage fluid, and ascites, by dividing them into cellular and acellular components. In addition, we reviewed previous studies on the diagnostic, prognostic, and predictive biomarkers for gastric cancer using liquid biopsy and discussed the limitations of liquid biopsy and the challenges to overcome these limitations in patients with gastric cancer.

Targeting the Tumor Microenvironment in Breast Cancer: Prognostic and Predictive Significance and Therapeutic Opportunities

Breast cancer is one of the most prevalent tumors among women. Its prognosis and treatment outcomes depend on factors related to tumor cell biology. However, recent studies have revealed the critical role of the tumor microenvironment (TME) in the development, progression, and treatment response of breast cancer. In this review, we explore the different components of the TME and their relevance as prognostic and predictive biomarkers in breast cancer. In addition, techniques for assessing the tumor microenvironment, such as immunohistochemistry or gene expression profiling, and their clinical utility in therapeutic decision-making are examined. Finally, therapeutic strategies targeting the TME are reviewed, highlighting their potential clinical benefits. Overall, this review emphasizes the importance of the TME in breast cancer and its potential as a clinical tool for better patient stratification and the design of personalized therapies.

ATM deficiency confers specific therapeutic vulnerabilities in bladder cancer.

Ataxia-telangiectasia mutated (ATM) plays a central role in the cellular response to DNA damage and ATM alterations are common in several tumor types including bladder cancer. However, the specific impact of ATM alterations on therapy response in bladder cancer is uncertain. Here, we combine preclinical modeling and clinical analyses to comprehensively define the impact of ATM alterations on bladder cancer. We show that ATM loss is sufficient to increase sensitivity to DNA-damaging agents including cisplatin and radiation. Furthermore, ATM loss drives sensitivity to DNA repair-targeted agents including poly(ADP-ribose) polymerase (PARP) and Ataxia telangiectasia and Rad3 related (ATR) inhibitors. ATM loss alters the immune microenvironment and improves anti-PD1 response in preclinical bladder models but is not associated with improved anti-PD1/PD-L1 response in clinical cohorts. Last, we show that ATM expression by immunohistochemistry is strongly correlated with response to chemoradiotherapy. Together, these data define a potential role for ATM as a predictive biomarker in bladder cancer.

Multistain deep learning as a prognostic and predictive biomarker in colorectal cancer

The tumor immune microenvironment (TIME) plays acrucial prognostic and predictive role in solid malignancies such as colorectal cancer (CRC). Nevertheless, scoring systems based on TIME such as the Immunoscore (IS) are rarely used in clinical practice. Among other reasons, this might be due to the additional time required for manual quantification of tumor-associated immune cells or costs associated with proprietary/commercial solutions. To address these issues, we developed amultistain deep learning model (MSDLM) and trained, validated, and tested it on immunohistochemical image data of different immune cell subtypes from over 1000 patients with CRC. Our model showed high prognostic accuracy and outperformed other clinical, molecular, and immune cell-based parameters. It might also be used for therapy response prediction in rectal cancer patients undergoing neoadjuvant therapy. Leveraging artificial intelligence interpretability/explainability methods, we ascertained that the MSDLM's predictions align with recognized antitumor immune response patterns. Consequently, the AImmunoscore (AIS) could emerge as apotential TIME-based decision-making tool for clinicians.

Investigating Torsin‐1A‐interacting protein 1 as a predictive and immunological biomarker in cancer

AbstractBackgroundCancer poses a significant global challenge, and with the projected rise in cancer incidence, there is an urgent need to discover new targets and treatments to improve patient outcomes. Recent advancements in genomics technologies have enhanced our understanding of cancer's complexities and led to the emergence of pan‐cancer analysis as a valuable approach for identifying tumor targets. Torsin‐1A‐interacting protein 1 (TOR1AIP1) is a membrane protein involved in various cellular processes. Emerging evidence suggests its potential involvement in cancer.MethodsIn this study, we conducted a comprehensive analysis of multiple databases to explore TOR1AIP1 expression across different cancer types and stages. We also investigated its correlation with clinical outcomes, such as survival rates and drug sensitivity.ResultsThe results of our analysis showed significant deregulation of TOR1AIP1 expression in multiple cancer types and its association with clinical outcomes, with a particular emphasis on kidney renal clear cell carcinoma. The results of our study highlight the potential predictive value of TOR1AIP1 in cancer prognosis and therapy.ConclusionsThis study establishes a solid foundation and rationale for future experimental investigations, which will contribute to a deeper understanding of the significance of TOR1AIP1 in different cancer types, specifically in kidney renal clear cell carcinoma.

Expression of Soluble Form of Aurora A as a Predictive Factor for Neoadjuvant Therapy in Breast Cancer Patients: A Single-Center Pilot Study.

To search for new predictive breast cancer biomarkers. We analyzed the serum concentrations of biomarkers involved in carcinogenesis, which can also be targeted by therapy. In a single-center prospective study, the serum levels of Aurora A, thymidine kinase 1, and human epidermal growth factor receptor type 3 (HER3) were determined in 119 women with BC before neoadjuvant treatment using ELISA kits. The following clinical data were analyzed: age; TNM; the expression of ER, PGR, HER2, and Ki67; histological grade (G); and the response to neoadjuvant treatment (NAT) in the residual tumor burden classification (RCB). A complete pathological response (pCR) was achieved after NAT in 41 patients (34%). The highest proportion of the patients with a confirmed pCR was found for triple negative breast cancer (TNBC) (62.5%); non-luminal HER2-positive (52.6%) cancer subtypes (p = 0.0003); and in the G3 group (50%; p = 0.0078). The patients with higher levels of Aurora A were more likely to achieve pCR (p = 0.039). In the multivariate analysis, the serum Aurora A levels ≥ 4.75 ng/mL correlated with a higher rate of pCR (OR: 3.5; 95% CI: 1.2-10.1; p = 0.023). We showed that in a biologically heterogeneous group of BC patients, the pretreatment serum Aurora A levels were of significant value in predicting the response to NAT.

Multidimensional progressive single-cell sequencing reveals cell microenvironment composition and cancer heterogeneity in lung cancer.

Despite substantial advances in cancer biology and treatment, the clinical outcomes of patients with lung cancer remain unsatisfactory. The tumor microenvironment (TME) is a potential target. Using single-cell RNA sequencing, we could distinguish eight distinct cell types in the lung cancer microenvironment, demonstrating substantial intratumoral heterogeneity in 19 different lung cancer tumor samples. Through the re-dimensional grouping of cancer-associated fibroblasts (CAFs), myeloid cells, epithelial cells, natural killer (NK) cells, and T cells, the difference in the TME of lung cancer was revealed. We discovered SFTPB, SFN, and KRT8 as possible predictive biomarkers for lung cancer by assessing the gene expression patterns in epithelial cells. Examining cell-to-cell communications showed a robust association between the quantity of matrix CAFs, epithelial cells, and macrophages in the thrombospondin signaling pathway. Additionally, we found that the amyloid precursor protein signaling pathway primarily originated from the matrix, and inflammatory cancer-associated endothelial and fibroblast cells showed a co-expression relationship with myeloid cells and B cells. Through cell-to-cell correlation analysis, we found positive regulation between NK cells, regulatory T cells, GZMB-CD8 T cells, and GZMK-CD8 T cells, which could play a role in developing immune TMEs. These findings support studies on cancer heterogeneity and add to our understanding of lung cancer's cellular microenvironment.

The Value of Tumor Infiltrating Lymphocytes (TIL) for Predicting the Response to Neoadjuvant Chemotherapy (NAC) in Breast Cancer according to the Molecular Subtypes.

The antitumor host immune response is an important factor in breast cancer, but its role is not fully established. The role of tumor infiltrating lymphocytes (TIL) as an immunological biomarker in breast cancer has been significantly explored in recent years. The number of patients treated with neoadjuvant chemotherapy (NAC) has increased and the identification of a biomarker to predict the probability of pCR (pathological complete response) is a high priority. We evaluated 334 cases of BC treated with NAC followed by surgical resection from 2020-2022 at the Ist Clinic of Oncological Surgery, Oncological Institute "Prof Dr I Chiricuta" Cluj Napoca. Of the above, 122 cases were available for histological evaluation both in pre-NAC biopsy and post-NAC resection tissue. Evaluation of biopsy fragments and resection parts were performed using hematoxylin eosin (H&E). The TIL evaluation took place according to the recommendations of the International TIL Working Group (ITILWG). There was a strong association between elevated levels of pre-NAC TIL. At the same time, there is a statistically significant correlation between stromal TIL and tumor grade, the number of lymph node metastases, the molecular subtype and the number of mitoses (p < 0.005). Intratumoral TIL showed a significant correlation with tumor size, distant metastasis, molecular subtype, number of mitosis, stage and lymph node metastasis (p < 0.005). We also demonstrated that high pre-NAC STIL represents a strong predictive marker for pCR. This study reveals the role of TIL as a predictive biomarker in breast cancer not only for the well-established TNBC (triple negative breast cancer) and HER2+ (Her2 overexpressed) subtypes but also in Luminal A and B molecular subtypes. In this scenario, the evaluation of sTIL as a novel predictive and therapy-predicting factor should become a routinely performed analysis that could guide clinicians when choosing the most appropriate therapy.

Identification of exosome protein panels as predictive biomarkers for non-small cell lung cancer

BackgroundNon-small cell lung cancer (NSCLC) remains a leading cause of cancer-related deaths worldwide, primarily due to its propensity for metastasis. Patients diagnosed with localized primary cancer have higher survival rates than those with metastasis. Thus, it is imperative to discover biomarkers for the early detection of NSCLC and the timely prediction of tumor metastasis to improve patient outcomes.MethodsHere, we utilized an integrated approach to isolate and characterize plasma exosomes from NSCLC patients as well as healthy individuals. We then conducted proteomics analysis and parallel reaction monitoring to identify and validate the top-ranked proteins of plasma exosomes.ResultsOur study revealed that the proteome in exosomes from NSCLC patients with metastasis was distinctly different from that from healthy individuals. The former had larger diameters and lower concentrations of exosomes than the latter. Furthermore, among the 1220 identified exosomal proteins, we identified two distinct panels of biomarkers. The first panel of biomarkers (FGB, FGG, and VWF) showed potential for early NSCLC diagnosis and demonstrated a direct correlation with the survival duration of NSCLC patients. The second panel of biomarkers (CFHR5, C9, and MBL2) emerged as potential biomarkers for assessing NSCLC metastasis, of which CFHR5 alone was significantly associated with the overall survival of NSCLC patients.ConclusionsThese findings underscore the potential of plasma exosomal biomarkers for early NSCLC diagnosis and metastasis prediction. Notably, CFHR5 stands out as a promising prognostic indicator for NSCLC patients. The clinical utility of exosomal biomarkers offers the potential to enhance the management of NSCLC.