Predictive power of tertiary lymphoid structure signature for neoadjuvant chemotherapy response and immunotherapy benefit in HER2-negative breast cancer.
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ABSTRACT:
SUBMITTER: Bertucci F
PROVIDER: S-EPMC10397558 | biostudies-literature | 2023 Aug
REPOSITORIES: biostudies-literature
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Predictive power of tertiary lymphoid structure signature for neoadjuvant chemotherapy response and immunotherapy benefit in HER2-negative breast cancer.
Bertucci François F De Nonneville Alexandre A Finetti Pascal P Mamessier Emilie E
Cancer communications (London, England) 20230606 8
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Project description:Ovarian cancer (OC) has the lowest survival rate among gynecologic malignancies. Ectopic lymphocyte aggregates, namely tertiary lymphoid structures (TLSs), have been reported as positive biomarkers for tumor prognosis. However, the related gene signature of tertiary lymphoid structure in ovarian cancer was less understood. Therefore, this study first exhibited the organizational patterns of tertiary lymphoid structure by H&E staining and immunohistochemistry (IHC), and confirmed the improved survival values of tertiary lymphoid structure and quantified tumor-infiltrating lymphocytes (CD20+ B cells and CD8+ T cells) in ovarian cancer patients. Secondly, we collected the genes involved in tertiary lymphoid structure from databases. By the univariate regression analysis, the tertiary lymphoid structure gene signature (CETP, CCR7, SELL, LAMP3, CCL19, CXCL9, CXCL10, CXCL11, and CXCL13) with prognostic value, characteristically of ovarian cancer, was constructed in the TCGA dataset and validated in the GSE140082 dataset. Thirdly, by performing CIBERSORT and Tumor Immune Dysfunction and Exclusion (TIDE) analysis, we found that the high expression of this gene signature was positively correlated with developed immune infiltration and reduced immune escape. The improved IPS score and application in the IMvigor210 dataset received PD-L1 proved the predictive value of immunotherapy for this gene signature. Furthermore, this signature showed a better correlation between tumor mutation burden and classical checkpoint genes. In conclusion, Tertiary lymphoid structure plays important role in tumor immunity and the gene signature can be evaluated as a biomarker for predicting prognosis and guiding immunotherapy in ovarian cancer.
| S-EPMC9871364 | biostudies-literature
Project description:ObjectiveThe present study aimed to evaluate the predictive factors that predict outcomes of HER2-low breast cancer patients who did not achieve pathological complete response(pCR) after neoadjuvant chemotherapy (NAC).MethodsThis study included patients with HER2-low breast cancer who received NAC from January 2017 to December 2020. Analysis of the clinicopathological features, NAC response and outcome of the patients were retrospectively analyzed. Univariate and multivariable Cox analysis were used to determine factors that predict outcomes of HER2-low breast cancer patients who did not exhibit pCR.Results293 Asian patients were included. The proportion of patients with hormone receptor (HR) positive and triple negative breast cancer (TNBC) among HER2-low patients was 75.8% and 24.2%, respectively. The pCR rate of HR positive cases was significantly lower than TNBC (27.5% vs. 53.5%, P=0.000). The patients who obtained pCR after NAC showed better disease-free survival(DFS) (5-year DFS 93.9% vs. 83.1%, p=0.039). For patients not achieving pCR, multivariable analysis showed that Miller/Payne (MP) grading system (hazard ratio: 0.094; 95% CI: 0.037-0.238; p=0.000) and HR status (hazard ratio: 2.561; 95% CI: 1.100-5.966; p=0.029) were significant independent predictors for DFS. Additionally, The MP grading system was also an independent predictor of overall survival (OS) (hazard ratio: 0.071; 95% CI: 0.019-0.260; p=0.000).ConclusionsThe results of our study show that pathological assessment following NAC offers valuable insights into the survival outcome of HER2-low breast cancer. According to these findings, responses to NAC should be considered when choosing systemic treatment for patients with HER2-low breast cancer.
| S-EPMC11920645 | biostudies-literature
Project description:BackgroundIt is encountering the dilemma of lacking precise biomarkers to predict the response to neoadjuvant chemoimmunotherapy (NACI) and determine whether patients should use immune checkpoint inhibitors (ICIs) in early breast cancer (BC). We aimed to develop a gene signature to predict NACI response for BC patients and identify individuals suitable for adding ICIs.Patients and methodsTwo I-SPY2 cohorts and one West China Hospital cohort of patients treated with NACI were included. Machine learning algorithms were used to identify key genes. Principal component analysis was used to calculate the ImPredict (IP) score. The interaction effects between biomarkers and treatment regimens were examined based on the logistic regression analysis. The relationship between the IP score and immune microenvironment was investigated through immunohistochemistry (IHC) and multiplex IHC.ResultsThe area under the curves of the IP score were 0.935, 0.865, and 0.841 in the discovery cohort, validation cohort 1, and in-house cohort. Marker-treatment interaction tests indicated that the benefits from immunotherapy significantly varied between patients with high and low IP scores (p for interaction <0.001), and patients with high IP scores were more suitable for immunotherapy addition.ConclusionsOur IP model shows favorable performance in predicting NACI response and is an effective tool for identifying BC patients who will benefit from ICIs. It may help clinicians optimize treatment strategies and guide clinical decision-making.
| S-EPMC11337705 | biostudies-literature
Project description:Antiangiogenic therapy using bevacizumab has proven effective for a number of cancers; however, in breast cancer (BC), there is an unmet need to identify patients who benefit from such treatment. In the NeoAva phase II clinical trial, patients (N = 132) with large (≥ 25 mm) human epidermal growth factor receptor 2 (HER2)-negative primary tumors were randomly assigned 1:1 to treatment with neoadjuvant chemotherapy (CTx) alone or in combination with bevacizumab (Bev plus CTx). The ratio of the tumor size after relative to before treatment was calculated into a continuous response scale. Tumor biopsies taken prior to neoadjuvant treatment were analyzed by reverse-phase protein arrays (RPPA) for expression levels of 210 BC-relevant (phospho-) proteins. Lasso regression was used to derive a predictor of tumor shrinkage from the expression of selected proteins prior to treatment. We identified a nine-protein signature score named vascular endothelial growth factor inhibition response predictor (ViRP) for use in the Bev plus CTx treatment arm able to predict with accuracy pathologic complete response (pCR) (area under the curve [AUC] = 0.85; 95% CI, 0.74 to 0.97) and low residual cancer burden (RCB 0/I) (AUC = 0.80; 95% CI, 0.68 to 0.93). The ViRP score was significantly lower in patients with pCR (P < .001) and in patients with low RCB (P < .001). The ViRP score was internally validated on mRNA data and the resultant surrogate mRNA ViRP score significantly separated the pCR patients (P = .016). Similarly, the mRNA ViRP score was validated (P < .001) in an independent phase II clinical trial (PROMIX). Our ViRP score, integrating the expression of nine proteins and validated on mRNA data both internally and in an independent clinical trial, may be used to increase the likelihood of benefit from treatment with bevacizumab combined with chemotherapy in patients with HER2-negative BC.
| S-EPMC8140811 | biostudies-literature
Project description:BackgroundThe clinical benefit of adjuvant chemotherapy for stage II colorectal cancer (CRC) is controversial. This study aimed to explore novel gene signature to predict outcome benefit of postoperative 5-Fu-based therapy in stage II CRC.MethodsGene-expression profiles of stage II CRCs from two datasets with 5-Fu-based adjuvant chemotherapy (training dataset, n = 212; validation dataset, n = 85) were analyzed to identify the indicator. A systemic approach by integrating gene-expression and protein-protein interaction (PPI) network was implemented to develop the predictive signature. Kaplan-Meier curves and Cox proportional hazards model were used to determine the survival benefit of adjuvant chemotherapy. Experiments with shRNA knock-down were carried out to confirm the signature identified in this study.ResultsIn the training dataset, we identified 44 PPI sub-modules, by which we separate patients into two clusters (1 and 2) having different chemotherapeutic benefit. A predictor of 11 PPI sub-modules (11-PPI-Mod) was established to discriminate the two sub-groups, with an overall accuracy of 90.1%. This signature was independently validated in an external validation dataset. Kaplan-Meier curves showed an improved outcome for patients who received adjuvant chemotherapy in Cluster 1 sub-group, but even worse survival for those in Cluster 2 sub-group. Similar results were found in both the training and the validation dataset. Multivariate Cox regression revealed an interaction effect between 11-PPI-Mod signature and adjuvant therapy treatment in the training dataset (RFS, p = 0.007; OS, p = 0.006) and the validation dataset (RFS, p = 0.002). From the signature, we found that PTGES gene was up-regulated in CRC cells which were more resistant to 5-Fu. Knock-down of PTGES indicated a growth inhibition and up-regulation of apoptotic markers induced by 5-Fu in CRC cells.ConclusionsOnly a small proportion of stage II CRC patients could benefit from adjuvant therapy. The 11-PPI-Mod as a potential predictor could be helpful to distinguish this sub-group with favorable outcome.
| S-EPMC5729289 | biostudies-literature
Project description:Treatment with immune checkpoint blockade (ICB) has revolutionized cancer therapy. Until now, predictive biomarkers1-10 and strategies to augment clinical response have largely focused on the T cell compartment. However, other immune subsets may also contribute to anti-tumour immunity11-15, although these have been less well-studied in ICB treatment16. A previously conducted neoadjuvant ICB trial in patients with melanoma showed via targeted expression profiling17 that B cell signatures were enriched in the tumours of patients who respond to treatment versus non-responding patients. To build on this, here we performed bulk RNA sequencing and found that B cell markers were the most differentially expressed genes in the tumours of responders versus non-responders. Our findings were corroborated using a computational method (MCP-counter18) to estimate the immune and stromal composition in this and two other ICB-treated cohorts (patients with melanoma and renal cell carcinoma). Histological evaluation highlighted the localization of B cells within tertiary lymphoid structures. We assessed the potential functional contributions of B cells via bulk and single-cell RNA sequencing, which demonstrate clonal expansion and unique functional states of B cells in responders. Mass cytometry showed that switched memory B cells were enriched in the tumours of responders. Together, these data provide insights into the potential role of B cells and tertiary lymphoid structures in the response to ICB treatment, with implications for the development of biomarkers and therapeutic targets.
| S-EPMC8762581 | biostudies-literature
Project description:The formation of TLSs induced by oncolytic virus treatment can enhance the anti-tumor response of oral cancer. Therefore, oncolytic virotherapy in vivo is a good strategy. To understand the mechanism of post-treatment changes, we collected oHSV-treated tumors for RNA-seq.
2025-01-08 | GSE262913 | GEO
Project description:BackgroundWe have previously shown that podocalyxin-like protein (PODXL) is a prognostic biomarker for poor survival in gastric and esophageal adenocarcinoma treated with surgery up-front. The aim of the present study was to assess PODXL expression in tumors from patients treated with neoadjuvant ± adjuvant (i.e. preoperative with or without postoperative) chemotherapy, with regard to histopathologic response, time to recurrence (TTR) and overall survival (OS).MethodsThe neoadjuvant cohort encompasses 148 consecutive patients who received neoadjuvant ± adjuvant chemotherapy for resectable gastric or esophageal adenocarcinoma between 2008 and 2014. Immunohistochemical expression of PODXL was assessed in pre-neoadjuvant biopsies, resected primary tumors and lymph node metastases. Histopathologic response was evaluated using the Chirieac grading. TTR and OS were estimated using Kaplan-Meier and Cox regression analyses. To investigate a potential predictive role for PODXL, the neoadjuvant cohort was pooled with the previously reported surgery up-front cohort.ResultsThe majority (> 95%) of the patients were treated with fluoropyrimidine- and oxaliplatin-based chemotherapy. Patients with high PODXL expression in their pre-neoadjuvant biopsies had a superior histopathologic response (notably 36% with no residual cancer cells) compared to those with negative or low PODXL expression, and were all recurrence-free at last follow-up. In the pooled cohort, no benefit of chemotherapy could be shown for PODXL negative cases, whereas PODXL positive (low or high) cases had a prolonged TTR and OS when treated with neoadjuvant ± adjuvant chemotherapy compared to surgery alone. The potential predictive role of PODXL was further strengthened for TTR in Cox regression analyses, especially for patients treated with neoadjuvant fluoropyrimidine and oxaliplatin for a minimum of 8 weeks, with a significant interaction term in both unadjusted (p = 0.006) and adjusted (p = 0.024) analyses. The interaction term was not statistically significant for overall survival.ConclusionsPatients with resectable gastric or esophageal adenocarcinoma with high PODXL expression in their diagnostic biopsies have an excellent prognosis when treated with neoadjuvant ± adjuvant fluoropyrimidine- and oxaliplatin-based chemotherapy. If the suggested predictive role of PODXL for benefit of chemotherapy can be confirmed, patients with PODXL negative tumors could be spared chemotherapy and treated with surgery alone.
| S-EPMC6201481 | biostudies-literature
Project description:PurposeThe tertiary lymphoid structure (TLS) is an important source of tumor-infiltrating lymphocytes (TILs), which have a strong prognostic and predictive value in triple-negative breast cancer (TNBC). A previous study reported that the levels of CXCL13 mRNA expression were associated with TLSs, but measuring the gene expression is challenging in routine practice. Therefore, this study evaluated the MECA79-positive high endothelial venule (HEV) densities and their association with the histopathologically assessed TLSs in biopsy samples. In addition, the relationship of TLSs with the CXCL13 transcript levels and clinical outcomes were examined.Materials and methodsA total of 108 TNBC patients treated with neoadjuvant chemotherapy (NAC) were studied. The amounts of TILs and TLSs were measured histopathologically using hematoxylin and eosin-stained slides. The HEV densities and TIL subpopulations were measured by immunohistochemistry for MECA79, CD3, CD8, and CD20. CXCL13mRNA expression levels using a NanoString assay (NanoString Technologies).ResultsThe mean number of HEVs in pre-NAC biopsies was 12 (range, 0 to 72). The amounts of TILs and TLSs, HEV density, and CXCL13 expression showed robust correlations with each other. A lower pre-NAC clinical T stage, higher TIL and TLS levels, a higher HEV density, CD20-positive cell density, and CXCL13 expression were significant predictors of a pathologic complete response (pCR). Higher CD8-positive cell density and levels of CXCL13 expression were significantly associated with a better disease-free survival rate.ConclusionMECA79-positive HEV density in pre-NAC biopsies is an objective and quantitative surrogate marker of TLS and might be a valuable tool for predicting pCR of TNBC in routine pathology practice.
| S-EPMC5398384 | biostudies-literature
Project description: Not available
| S-EPMC8703124 | biostudies-literature