Stromal Clusterin Expression Predicts Therapeutic Response to Neoadjuvant Chemotherapy in Triple Negative Breast Cancer

Apolipoproteins have a major role in cellular tumor dormancy in triple negative breast cancer: In-silico study

Triple-negative breast cancer (TNBC) lacks estrogen, progesterone, and human epidermal growth factor receptors and has a poor prognosis as it is resistant to chemotherapy. A new treatment option for this type of cancer may be by putting these malignant cells into dormancy. The oocyte's embryonic milieu presents a unique tumor reversion microenvironment by inducing growth arrest and changing cells' phenotypes. We conducted an in-silico study to determine the most likely oocyte extract (OE) proteins involved in inducing dormancy using HDock, CluPro, and molecular dynamic (MD) simulation. Results showed low energy scores for complexes between OE proteins and four surface markers: K1C14, CLD3, CLD4, and ITA6. Apolipoprotein A1 (APOA1) and Apolipoprotein C3 (APOC3) showed the highest stability and affinity with these four surface markers: K1C14, CLD3, CLD4, and ITA6. These proteins are involved in key tumor-related pathways such as angiogenesis, proliferation, apoptosis, and migration. This will pave the way for exploring novel therapeutic options to induce dormancy in TNBC cells.

Decoding CLU (Clusterin): Conquering cancer treatment resistance and immunological barriers

One major obstacle in the treatment of cancer is the presence of proteins resistant to cancer therapy, which can impede the effectiveness of traditional approaches such as radiation and chemotherapy. This resistance can lead to disease progression and cause treatment failure. Extensive research is currently focused on studying these proteins to create tailored treatments that can circumvent resistance mechanisms. CLU (Clusterin), a chaperone protein, has gained notoriety for its role in promoting resistance to a wide range of cancer treatments, including chemotherapy, radiation therapy, and targeted therapy. The protein has also been discovered to have a role in regulating the immunosuppressive environment within tumors. Its ability to influence oncogenic signaling and inhibit cell death bolster cancer cells resistant against treatments, which poses a significant challenge in the field of oncology. Researchers are actively investigating to the mechanisms by which CLU exerts its resistance-promoting effects, with the ultimate goal of developing strategies to circumvent its impact and enhance the effectiveness of cancer therapies. By exploring CLU's impact on cancer, resistance mechanisms, tumor microenvironment (TME), and therapeutic strategies, this review aims to contribute to the ongoing efforts to improve cancer treatment outcomes.

Predictive value of tumor-infiltrating lymphocytes for neoadjuvant therapy response in triple-negative breast cancer: A systematic review and meta-analysis

BACKGROUND

The association between tumor-infiltrating lymphocyte (TIL) levels and the response to neoadjuvant therapy (NAT) in patients with triple-negative breast cancer (TNBC) remains unclear.

AIM

To investigate the predictive potential of TIL levels for the response to NAT in TNBC patients.

METHODS

A systematic search of the National Center for Biotechnology Information PubMed database was performed to collect relevant published literature prior to August 31, 2023. The correlation between TIL levels and the NAT pathologic complete response (pCR) in TNBC patients was assessed using a systematic review and meta-analysis. Subgroup analysis, sensitivity analysis, and publication bias analysis were also conducted.

RESULTS

A total of 32 studies were included in this meta-analysis. The overall meta-analysis results indicated that the pCR rate after NAT treatment in TNBC patients in the high TIL subgroup was significantly greater than that in patients in the low TIL subgroup (48.0% vs 27.7%) (risk ratio 2.01; 95% confidence interval 1.77-2.29; P < 0.001, I 2 = 56%). Subgroup analysis revealed that the between-study heterogeneity originated from differences in study design, TIL level cutoffs, and study populations. Publication bias could have existed in the included studies. The meta-analysis based on different NAT protocols revealed that all TNBC patients with high levels of TILs had a greater rate of pCR after NAT treatment in all protocols (all P ≤ 0.01), and there was no significant between-protocol difference in the statistics among the different NAT protocols (P = 0.29). Additionally, sensitivity analysis demonstrated that the overall results of the meta-analysis remained consistent when the included studies were individually excluded.

CONCLUSION

TILs can serve as a predictor of the response to NAT treatment in TNBC patients. TNBC patients with high levels of TILs exhibit a greater NAT pCR rate than those with low levels of TILs, and this predictive capability is consistent across different NAT regimens.

Triple-Negative Breast Cancer and Predictive Markers of Response to Neoadjuvant Chemotherapy: A Systematic Review

Around 40-50% of all triple-negative breast cancer (TNBC) patients achieve a pathological complete response (pCR) after treatment with neoadjuvant chemotherapy (NAC). The identification of biomarkers predicting the response to NAC could be helpful for personalized treatment. This systematic review provides an overview of putative biomarkers at baseline that are predictive for a pCR following NAC. Embase, Medline and Web of Science were searched for articles published between January 2010 and August 2022. The articles had to meet the following criteria: patients with primary invasive TNBC without distant metastases and patients must have received NAC. In total, 2045 articles were screened by two reviewers resulting in the inclusion of 92 articles. Overall, the most frequently reported biomarkers associated with a pCR were a high expression of Ki-67, an expression of PD-L1 and the abundance of tumor-infiltrating lymphocytes, particularly CD8+ T cells, and corresponding immune gene signatures. In addition, our review reveals proteomic, genomic and transcriptomic markers that relate to cancer cells, the tumor microenvironment and the peripheral blood, which also affect chemo-sensitivity. We conclude that a prediction model based on a combination of tumor and immune markers is likely to better stratify TNBC patients with respect to NAC response.

Next Generation Sequencing of Reactive Stroma and Residual Breast Cancer Cells in Tumor Bed after Neoadjuvant Chemotherapy

Primary systemic or neoadjuvant chemotherapy of breast cancer has become a standard therapy option in locally advanced or predefined intrinsic subtypes such as triple negative or Her2 positive breast cancer. Neoadjuvant chemotherapy can result in complete pathological response without residual tumor cells (tumor bed) or partial response and non-response with different amounts of reactive stroma and residual tumor cells. The interaction between therapy regimens and tumoral driver mutations have been extensively studied, although the reactive stroma of the tumor bed received less attention. In this study, we characterized the mutational status of residual breast cancer cells and reactive tumor stroma devoid of residual tumor cells in partial or non-responders using next generation sequencing. Twenty-one post-therapeutic breast surgical specimens after neoadjuvant chemotherapy underwent pathogenic driver-mutation screening using microdissected residual breast cancer cells and in reactive stroma adjacent to tumor bed areas. In reactive stroma, no mutations could be validated. In residual breast cancer cells, mutations were detected in sixteen of twenty-one cases (76%). In nine of these twenty-one cases (43%), pathogenic driver mutations (PIK3CA, PTEN, TP53, FN1, PLAG1) were identified. Pathogenic driver-mutations are exclusively restricted to residual carcinoma cells and are absent in reactive stroma independently from intrinsic breast cancer subtypes or tumor stage. These data suggest that the absence of pathogenic mutations in a tumor bed without residual tumor cells may have prognostic implications after neoadjuvant chemotherapy.

BRCA mutational status shapes the stromal microenvironment of pancreatic cancer linking clusterin expression in cancer associated fibroblasts with HSF1 signaling

Tumors initiate by mutations in cancer cells, and progress through interactions of the cancer cells with non-malignant cells of the tumor microenvironment. Major players in the tumor microenvironment are cancer-associated fibroblasts (CAFs), which support tumor malignancy, and comprise up to 90% of the tumor mass in pancreatic cancer. CAFs are transcriptionally rewired by cancer cells. Whether this rewiring is differentially affected by different mutations in cancer cells is largely unknown. Here we address this question by dissecting the stromal landscape of BRCA-mutated and BRCA Wild-type pancreatic ductal adenocarcinoma. We comprehensively analyze pancreatic cancer samples from 42 patients, revealing different CAF subtype compositions in germline BRCA-mutated vs. BRCA Wild-type tumors. In particular, we detect an increase in a subset of immune-regulatory clusterin-positive CAFs in BRCA-mutated tumors. Using cancer organoids and mouse models we show that this process is mediated through activation of heat-shock factor 1, the transcriptional regulator of clusterin. Our findings unravel a dimension of stromal heterogeneity influenced by germline mutations in cancer cells, with direct implications for clinical research.

An Aging-Related Gene Signature-Based Model for Risk Stratification and Prognosis Prediction in Breast Cancer

BACKGROUND

Aging, an inevitable process characterized by functional decline over time, is a significant risk factor for various tumors. However, little is known about aging-related genes (ARGs) in breast cancer (BC). We aimed to explore the potential prognostic role of ARGs and to develop an ARG-based prognosis signature for BC.

METHODS

RNA-sequencing expression profiles and corresponding clinicopathological data of female patients with BC were obtained from public databases in The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO). An ARG-based risk signature was constructed in the TCGA cohort based on results of least absolute shrinkage and selection operator (LASSO) and multivariate Cox regression analysis, and its prognostic value was further validated in the GSE20685 cohort.

RESULTS

A six ARG-based signature, including CLU, DGAT1, MXI1, NFKBI, PIK3CA and PLAU, was developed in the TCGA cohort and significantly stratified patients into low- and high-risk groups. Patients in the former group showed significantly better prognosis than those in the latter. Multivariate Cox regression analysis demonstrated that the ARG risk score was an independent prognostic factor for BC. A predictive nomogram integrating the ARG risk score and three identified factors (age, N- and M-classification) was established in the TCGA cohort and validated in the GSE20685 cohort. Calibration plots showed good consistency between predicted survival probabilities and actual observations.

CONCLUSION

A novel ARG-based risk signature was developed for patients with BC, which can be used for individual prognosis prediction and promoting personalized treatment.

Inflammation, Extracellular Matrix Remodeling, and Proteostasis in Tumor Microenvironment

Cancer is a multifaceted and complex pathology characterized by uncontrolled cell proliferation and decreased apoptosis. Most cancers are recognized by an inflammatory environment rich in a myriad of factors produced by immune infiltrate cells that induce host cells to differentiate and to produce a matrix that is more favorable to tumor cells’ survival and metastasis. As a result, the extracellular matrix (ECM) is changed in terms of macromolecules content, degrading enzymes, and proteins. Altered ECM components, derived from remodeling processes, interact with a variety of surface receptors triggering intracellular signaling that, in turn, cancer cells exploit to their own benefit. This review aims to present the role of different aspects of ECM components in the tumor microenvironment. Particularly, we highlight the effect of pro- and inflammatory factors on ECM degrading enzymes, such as metalloproteases, and in a more detailed manner on hyaluronan metabolism and the signaling pathways triggered by the binding of hyaluronan with its receptors. In addition, we sought to explore the role of extracellular chaperones, especially of clusterin which is one of the most prominent in the extracellular space, in proteostasis and signaling transduction in the tumor microenvironment. Although the described tumor microenvironment components have different biological roles, they may engage common signaling pathways that favor tumor growth and metastasis.

Diagnostic value of clusterin immunostaining in hepatocellular carcinoma

Background

Histologic distinction between well differentiated hepatocellular carcinoma (HCC) and benign hepatocellular mass lesions is a known challenge. Existing biomarkers are of limited diagnostic value. Our previous studies observed an enhanced canalicular expression pattern of clusterin (CLU) in HCC, which was not observed in benign hepatocellular mass lesions such as hepatocellular adenoma. The aim of this study was to further investigate its diagnostic value for HCC by examining the expression pattern of CLU in a large number of non-hepatocellular tumors, and by comparing it with two other commonly used hepatocellular markers pCEA and CD10 that also show a canalicular staining pattern in HCC.

Methods

Enhanced canalicular staining patterns of CLU, pCEA and CD10 were analyzed on 54 surgically resected well to moderately differentiated HCCs on whole tissue sections, of which 37 had surrounding regenerative nodules while the remaining 17 had a non-cirrhotic background. CLU immunostaining was also performed on tissue microarray sections that contained 74 HCCs (40 of which were also stained for pCEA and CD10), 55 normal liver tissue samples, and 1305 non-hepatocellular tumors from multiple organs.

Results

Enhanced CLU canalicular staining was observed in 70% (89/128) HCCs but not in regenerative nodules, normal liver tissues or any non-hepatocellular tumors. The sensitivity and specificity for enhanced canalicular staining pattern of CLU in HCCs were 0.70 and 1.00. This enhanced canalicular pattern was observed in only 26 and 23% HCCs for CD10 and pCEA, respectively. These results further demonstrate that the distinctive enhanced canalicular pattern of CLU is unique to HCC.

Conclusions

CLU is superior to pCEA and CD10 as a diagnostic immunomarker in that it can help distinguish well to moderately differentiated HCC not only from non-HCC malignancies but also from benign hepatocellular mass lesions.

Gene signature-based prediction of triple-negative breast cancer patient response to Neoadjuvant chemotherapy

Neoadjuvant chemotherapy is the current standard of care for large, advanced, and/or inoperable tumors, including triple‐negative breast cancer. Although the clinical benefits of neoadjuvant chemotherapy have been illustrated through numerous clinical trials, more than half of the patients do not experience therapeutic benefit and needlessly suffer from side effects. Currently, no clinically applicable biomarkers are available for predicting neoadjuvant chemotherapy response in triple‐negative breast cancer; the discovery of such a predictive biomarker or marker profile is an unmet need. In this study, we introduce a generic computational framework to calculate a response‐probability score (RPS), based on patient transcriptomic profiles, to predict their response to neoadjuvant chemotherapy. We first validated this framework in ER‐positive breast cancer patients and showed that it predicted neoadjuvant chemotherapy response with equal performance to several clinically used gene signatures, including Oncotype DX and MammaPrint. Then, we applied this framework to triple‐negative breast cancer data and, for each patient, we calculated a response probability score (TNBC‐RPS). Our results indicate that the TNBC‐RPS achieved the highest accuracy for predicting neoadjuvant chemotherapy response compared to previously proposed 143 gene signatures. When combined with additional clinical factors, the TNBC‐RPS achieved a high prediction accuracy for triple‐negative breast cancer patients, which was comparable to the prediction accuracy of Oncotype DX and MammaPrint in ER‐positive patients. In conclusion, the TNBC‐RPS accurately predicts neoadjuvant chemotherapy response in triple‐negative breast cancer patients and has the potential to be clinically used to aid physicians in stratifying patients for more effective neoadjuvant chemotherapy.

Bone marrow-derived fibroblasts are a functionally distinct stromal cell population in breast cancer

Raz et al. demonstrate that the expression of PDGFRα distinguishes two functional CAF populations in breast tumors and lung metastases and identify a subpopulation of CAFs that are specifically recruited to the tumor microenvironment from mesenchymal stromal cells in the BM.

Cancer-associated fibroblasts (CAFs) are highly prominent in breast tumors, but their functional heterogeneity and origin are still largely unresolved. We report that bone marrow (BM)–derived mesenchymal stromal cells (MSCs) are recruited to primary breast tumors and to lung metastases and differentiate to a distinct subpopulation of CAFs. We show that BM-derived CAFs are functionally important for tumor growth and enhance angiogenesis via up-regulation of Clusterin. Using newly generated transgenic mice and adoptive BM transplantations, we demonstrate that BM-derived fibroblasts are a substantial source of CAFs in the tumor microenvironment. Unlike resident CAFs, BM-derived CAFs do not express PDGFRα, and their recruitment resulted in a decrease in the percentage of PDGFRα-expressing CAFs. Strikingly, decrease in PDGFRα in breast cancer patients was associated with worse prognosis, suggesting that BM-derived CAFs may have deleterious effects on survival. Therefore, PDGFRα expression distinguishes two functionally unique CAF populations in breast tumors and metastases and may have important implications for patient stratification and precision therapeutics.