Additional file 2: of RAS status and neoadjuvant chemotherapy impact CD8+ cells and tumor HLA class I expression in liver metastatic colorectal cancer

Figure S1. Immune parameters correlation. Figure S2. Impact of Ras-Raf mutationnal status tumor environment. Figure S3. HLA score and CD8 positive cells combination as prognostic factor. Figure S4. Impact of neoadjuvant chemotherapy on immune infiltrates. Figure S5. CD8+ cells’ recruitment modifies tumor stroma making mCRC elligible for immune therapeutic intervention. (ZIP 430 kb

Table S1 from Exome Analysis Reveals Genomic Markers Associated with Better Efficacy of Nivolumab in Lung Cancer Patients

Table S1</p

Anti-MEK and Anti-EGFR mAbs in RAS-Mutant Metastatic Colorectal Cancer: Case Series and Rationale

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Additional file 1: of RAS status and neoadjuvant chemotherapy impact CD8+ cells and tumor HLA class I expression in liver metastatic colorectal cancer

Table S1. Progression Free Survival statistical summary. Table S2. Overall Survival statistical summary for WT patients. Table S3. Overall Survival statistical summary for RAS-RAF mutated patients. Table S4. List of antibodies used. (XLSX 20 kb

Figure S2 from Exome Analysis Reveals Genomic Markers Associated with Better Efficacy of Nivolumab in Lung Cancer Patients

Figure S2 Figure S2. Flowchart of the exome analysis. The cohort is composed of 77 patients; 65 have matched tumour and normal exomes, and 12 have only a tumour exome. When matched exomes are available, single-nucleotide variants, polymorphisms, mutational signatures, ploidy, large loss of heterozygosity (LOH) and deletions, copy number alteration (CNA) clonality, neoantigens, and T-cell receptor (TCR) clonality were analysed. TRC clonality could also be estimated for patients with a tumour exome only</p

Figure S6 from Exome Analysis Reveals Genomic Markers Associated with Better Efficacy of Nivolumab in Lung Cancer Patients

Figure S6 Figure S6. (A) Barplot showing the number of patients with at least one mutation in the MAPK, PI3K/AKT, or WNT pathways. (B-C) Kaplan-Meier estimates for progression-free survival (PFS) (B) and overall survival (OS) (C); patients were stratified according to the presence (activated; in blue) or absence (wild-type; in red) of somatic mutations in genes involved in the MAPK/PI3K/AKT pathways. (D) Kaplan-Meier estimates for PFS; patients were stratified according to the presence (activated; in blue) or absence (wild-type; in red) of mutations in genes involved in the WNT pathway. (E) Cumulative barplot showing the number of patients with mutations in the HR, NER, BER, POL, MMR, and NHEJ pathways: somatic mutations are in black, germline mutations are in white. (F) Boxplots representing the tumour mutational burden (TMB) per Mb for patients with altered genes involved in DNA repair pathways (altered; grey) or without altered genes in DNA repair pathways (wild-type; black), respectively. (G-H) Kaplan-Meier estimates for OS; patients were stratified according to the presence of somatic mutations (G) and pooled somatic and constitutional mutations (H) in genes involved in DNA repair pathways: wild-type (in red) and altered (in blue). (I) Kaplan-Meier estimates for OS; patients were stratified according to the DNA repair pathway state: single hit (only one mutation; in red) or double hit (in blue), which is at least two mutations or one mutation and one loss of heterozygosity. Only patients with at least one mutation in the DNA repair pathway were retained in this analysis. *: p < 0.05; **: p < 0.01; ***: p < 0.001; ****: p < 0.0001; ns: not significant.</p

Supplementary Methods from Exome Analysis Reveals Genomic Markers Associated with Better Efficacy of Nivolumab in Lung Cancer Patients

Supplementary Methods</p

Figure S7 from Exome Analysis Reveals Genomic Markers Associated with Better Efficacy of Nivolumab in Lung Cancer Patients

Figure S7 Figure S7. (A) Kaplan-Meier estimates for overall survival (OS); patients were stratified according to the number of neoantigens: low rate ({less than or equal to}51; in blue) or high rate (>51; in red). (B) Heat-map showing for each patient the presence/absence of each of the type I HLA phenotypes. Presence of a type I HLA phenotype is represented with a black square, and a white square represents the absence of this phenotype. (C) Scatterplots showing the number of bioinformatically detected T-cell receptor (TCR) clones for a given number of neoantigens. The rho value represents Spearman's rank correlation. (D) Kaplan-Meier estimates for OS; patients were stratified according to the number of TCR clones: between 1 and 4 clones (in red) or less than 1 or more than</p

Figure S3 from Exome Analysis Reveals Genomic Markers Associated with Better Efficacy of Nivolumab in Lung Cancer Patients

Figure S3 Figure S3. (A) Kaplan-Meier estimates for overall survival (OS); patients were stratified according to their tumor mutational burden (TMB) per Mb: low rate (in red) or high rate (in blue). (B-H) KaplanMeier estimates for OS; patients were stratified according to their proportion of signatures 1A (B), 1B (C), 3 (D), 4 (E), 6 (F), 16 (G), and 21 (H): low proportion (in red) or high proportion (in blue). The cutoffs were those defined for progression-free survival with the Cutoff Finder method. *: p < 0.05; **: p < 0.01; ***: p < 0. 001; ****: p < 0.0001; ns: not significant.</p

Characteristics of breast cancer subtypes of patients in Côte d’Or selected for the study (2003–2013).

<p>Characteristics of breast cancer subtypes of patients in Côte d’Or selected for the study (2003–2013).</p