Table_1_Correlation of the TIGIT-PVR immune checkpoint axis with clinicopathological features in triple-negative breast cancer.docx

BackgroundT cell immunoreceptor with Ig and ITIM domains (TIGIT) interacts with poliovirus receptor (PVR) to contribute to cancer immune escape. Recently, TIGIT and PVR have been identified as promising immunotherapy targets. Their gene expression is upregulated in many solid tumors, but their protein expression level is not well documented, particularly in triple negative breast cancer (TNBC), the breast cancer subtype that most benefit from immunotherapy.MethodsTIGIT and PVR expression levels were assessed by immunohistochemistry in 243 surgically resected localized TNBC and then their relationship with clinical-pathological features and clinical outcome was analyzed.ResultsTIGIT expression was observed in immune cells from the tumor microenvironment, whereas PVR was mainly expressed by tumor cells. High TIGIT expression was significantly associated with age (p=0.010), histological grade (p=0.014), non-lobular histology (p=0.024), adjuvant chemotherapy (p=0.006), and various immune cell populations (tumor infiltrating lymphocytes (TILs), CD3+, CD8+, PD-1+ cells; all p+ tumor cells (p+ stromal cells (p=0.003). Infiltration by TIGIT+ cells tended to be higher in non-molecular apocrine tumors (p=0.088). PVR was significantly associated with histological grade (p+ (p=0.002), CD8+ (p=0.024) T cells, and PD-L1 expression in tumor (p=0.003) and stromal cells (p=0.001). In univariate analysis, only known prognostic factors (age, tumor size, lymph node status, adjuvant chemotherapy, TILs and CD3+ T-cell infiltrate) were significantly associated with relapse-free survival (RFS) and overall survival. High TIGIT and PVR expression levels tended to be associated with longer RFS (p=0.079 and 0.045, respectively). The analysis that included only non-molecular apocrine TNBC revealed longer RFS for tumors that strongly expressed TIGIT or PVR (p=0.025 for TIGIT and 0.032 for PVR).ConclusionsThese results indicated that in TNBC, TIGIT+ cells can easily interact with PVR to exert their inhibitory effects. Their wide expression in TNBC and their association with other immune checkpoint components suggest the therapeutic interest of the TIGIT-PVR axis.</p

Image_1_Correlation of the TIGIT-PVR immune checkpoint axis with clinicopathological features in triple-negative breast cancer.tif

BackgroundT cell immunoreceptor with Ig and ITIM domains (TIGIT) interacts with poliovirus receptor (PVR) to contribute to cancer immune escape. Recently, TIGIT and PVR have been identified as promising immunotherapy targets. Their gene expression is upregulated in many solid tumors, but their protein expression level is not well documented, particularly in triple negative breast cancer (TNBC), the breast cancer subtype that most benefit from immunotherapy.MethodsTIGIT and PVR expression levels were assessed by immunohistochemistry in 243 surgically resected localized TNBC and then their relationship with clinical-pathological features and clinical outcome was analyzed.ResultsTIGIT expression was observed in immune cells from the tumor microenvironment, whereas PVR was mainly expressed by tumor cells. High TIGIT expression was significantly associated with age (p=0.010), histological grade (p=0.014), non-lobular histology (p=0.024), adjuvant chemotherapy (p=0.006), and various immune cell populations (tumor infiltrating lymphocytes (TILs), CD3+, CD8+, PD-1+ cells; all p+ tumor cells (p+ stromal cells (p=0.003). Infiltration by TIGIT+ cells tended to be higher in non-molecular apocrine tumors (p=0.088). PVR was significantly associated with histological grade (p+ (p=0.002), CD8+ (p=0.024) T cells, and PD-L1 expression in tumor (p=0.003) and stromal cells (p=0.001). In univariate analysis, only known prognostic factors (age, tumor size, lymph node status, adjuvant chemotherapy, TILs and CD3+ T-cell infiltrate) were significantly associated with relapse-free survival (RFS) and overall survival. High TIGIT and PVR expression levels tended to be associated with longer RFS (p=0.079 and 0.045, respectively). The analysis that included only non-molecular apocrine TNBC revealed longer RFS for tumors that strongly expressed TIGIT or PVR (p=0.025 for TIGIT and 0.032 for PVR).ConclusionsThese results indicated that in TNBC, TIGIT+ cells can easily interact with PVR to exert their inhibitory effects. Their wide expression in TNBC and their association with other immune checkpoint components suggest the therapeutic interest of the TIGIT-PVR axis.</p

Additional file 2: of Impact of vitamin D on pathological complete response and survival following neoadjuvant chemotherapy for breast cancer: a retrospective study

pCR rate depending on the VD level at baseline in the two HER2+ subgroups: a HR+/HER2+. b HR-/HER2+. (DOCX 15 kb

Additional file 1: Table S1. of High EGFR protein expression and exon 9 PIK3CA mutations are independent prognostic factors in triple negative breast cancers

Primers for PIK3CA exon 9 and 20 mutation analysis. (DOCX 17 kb

Additional file 4: of High EGFR protein expression and exon 9 PIK3CA mutations are independent prognostic factors in triple negative breast cancers

Relapse Free and Overall Survival. (PPTX 55 kb

BRCA1-methylated triple negative breast cancers previously exposed to neoadjuvant chemotherapy form RAD51 foci and respond poorly to olaparib

Background About 15% of Triple-Negative-Breast-Cancer (TNBC) present silencing of the BRCA1 promoter methylation and are assumed to be Homologous Recombination Deficient (HRD). BRCA1 -methylated ( BRCA1 -Me) TNBC could, thus, be eligible to treatment based on PARP-inhibitors or Platinum salts. However, their actual HRD status is discussed, as these tumors are suspected to develop resistance after chemotherapy exposure. Methods We interrogated the sensitivity to olaparib vs . carboplatin of 8 TNBC Patient-Derived Xenografts (PDX) models. Four PDX corresponded to BRCA1-Me , of which 3 were previously exposed to NeoAdjuvant-Chemotherapy (NACT). The remaining PDX models corresponded to two BRCA1 -mutated ( BRCA1-Mut ) and two BRCA1-wild type PDX that were respectively included as positive and negative controls. The HRD status of our PDX models was assessed using both genomic signatures and the functional BRCA1 and RAD51 nuclear foci formation assay. To assess HR restoration associated with olaparib resistance, we studied pairs of BRCA1 deficient cell lines and their resistant subclones. Results The 3 BRCA1 - Me PDX that had been exposed to NACT responded poorly to olaparib, likewise BRCA1-WT PDX. Contrastingly, 3 treatment-naïve BRCA1-deficient PDX (1 BRCA1 -Me and 2 BRCA1 -mutated) responded to olaparib. Noticeably, the three olaparib-responsive PDX scored negative for BRCA1- and RAD51-foci, whereas all non-responsive PDX models, including the 3 NACT-exposed BRCA1-Me PDX, scored positive for RAD51-foci. This suggested HRD in olaparib responsive PDX, while non-responsive models were HR proficient. These results were consistent with observations in cell lines showing a significant increase of RAD51-foci in olaparib-resistant subclones compared with sensitive parental cells, suggesting HR restoration in these models. Conclusion Our results thus support the notion that the actual HRD status of BRCA1-Me TNBC, especially if previously exposed to chemotherapy, may be questioned and should be verified using the BRCA1- and RAD51-foci assay

Additional file 1 of Multiple PIK3CA mutation clonality correlates with outcomes in taselisib + fulvestrant-treated ER+/HER2–, PIK3CA-mutated breast cancers

Additional file 1: PDF file, containing the article-associated supplementary tables and figures. Table S1. Clonality subgroup nomenclature and associated definitions for single and multiple PIK3CAPIK3CAmut; Table S2. Clonality estimation and tabulation of multiple PIK3CAPIK3CAmut identified in baseline ctDNA from SANDPIPER participants; Table S3. Clonality estimation and tabulation of single PIK3CAPIK3CAmut identified in baseline ctDNA from SANDPIPER participants; Table S4. Signaling pathway gene lists utilized in pathway-level analyses; Table S5. Fraction of samples with altered signaling pathway genes between SANDPIPER treatment groups; Table S6. Fraction of samples with altered signaling pathway genes between SANDPIPER treatment groups stratified by clonality status; Fig. S1. Gene alteration rates between SANDPIPER baseline ctDNA samples categorized as clonal vs subclonal single PIK3CAPIK3CAmut; Fig. S2. Pathway-level co-alteration analyses between ctDNA samples harboring clonal vs subclonal single PIK3CAPIK3CAmut; Fig. S3. Consort diagram for the clonality analysis of an independent breast tumor tissue dataset; Fig. S4. ORR and PFS of SANDPIPER participants whose baseline ctDNA samples harbored single PIK3CAPIK3CAmut