The prognostic significance of skin involvement in breast cancer patients with chest wall recurrence

To assess the prognostic significance of skin involvement in breast cancer patients with chest wall recurrence (CWR). We retrospectively analyzed the clinicopathological data of breast cancer patients with CWR who were diagnosed pathologically between January 2000 and April 2020. Disease-free survival (DFS) was the time from radical resection for CWR to disease recurrence. Progression-free survival (PFS) was defined as the time from the diagnosis of locally unresectable CWR to the first sign of disease progression. Persistent chest wall progression was defined as three consecutive chest wall progressions with no distant organ involvement. A total of 476 patients with CWR were included in this study. Skin involvement was confirmed in 345 patients. Skin involvement was significantly correlated with a high T stage (p = 0.003), more positive nodes at initial examination (p p p p p = 0.022). Multivariate analysis showed that skin involvement was an independent biomarker for DFS (p = 0.043). Patients with skin involvement were more likely to experience persistent chest wall progression (p = 0.040). After eliminating the potential deviation caused by an insufficient follow-up time, persistent chest wall progression was more likely to be associated with a high N stage (p = 0.002), negative progesterone receptor (PR; p = 0.001) and positive human epidermal growth factor receptor 2 (HER2; p = 0.046) of the primary site, and negative oestrogen receptor (ER; p = 0.027) and PR (p = 0.013) of the chest wall lesion and skin involvement (p = 0.020). Skin involvement was a predictor of poor disease control in patients with CWR and was closely related to persistent chest wall progression. We stratified the prognosis of individualized treatment for breast cancer patients with CWR to provide new insights into the biological behaviours of the disease. Skin involvement is a predictor of poor local disease control in breast cancer patients with CWR and a factor contributing to persistent chest wall progression after CWR. We stratified the prognosis of individualized treatment for breast cancer patients with CWR.</p

Clinical genomic profiling to identify actionable alterations for very early relapsed triple-negative breast cancer patients in the Chinese population

Triple-negative breast cancer (TNBC) represents about 19% of all breast cancer cases in the Chinese population. Lack of targeted therapy contributes to the poorer outcomes compared with other breast cancer subtypes. Comprehensive genomic profiling helps to explore the clinically relevant genomic alterations (CRGAs) and potential therapeutic targets in very-early-relapsed TNBC patients. Formalin-fixed paraffin-embedded (FFPE) tumour tissue specimens from 23 patients with very-early-relapsed TNBC and 13 patients with disease-free survival (DFS) more than 36 months were tested by FoundationOne CDx (F1CDx) in 324 genes and select gene rearrangements, along with genomic signatures including microsatellite instability (MSI) and tumour mutational burden (TMB). In total, 137 CRGAs were detected in the 23 very-early-relapsed TNBC patients, averaging six alterations per sample. The mean TMB was 4 Muts/Mb, which was higher than that in non-recurrence patients, and is statistically significant. The top-ranked altered genes were TP53 (83%), PTEN (35%), RB1 (30%), PIK3CA (26%) and BRCA1 (22%). RB1 mutation carriers had shorter DFS. Notably, 100% of these patients had at least one CRGA, and 87% of patients had at least one actionable alteration. In pathway analysis, patients who carried a mutation in the cell cycle pathway were more likely to experience very early recurrence. Strikingly, we detected one patient with ERBB2 amplification and one patient with ERBB2 exon20 insertion, both of which were missed by immunohistochemistry (IHC). We also detected novel alterations of ROS1–EPHA7 fusion for the first time, which has not been reported in breast cancer before. The comprehensive genomic profiling can identify novel treatment targets and address the limited options in TNBC patients. Therefore, incorporating F1CDx into TNBC may shed light on novel therapeutic opportunities for these very-early-relapsed TNBC patients.</p

DataSheet_1_Distribution Characteristics and Prognostic Value of Immune Infiltration in Oligometastatic Breast Cancer.docx

BackgroundTo assess the distribution characteristics and the prognostic value of immune infiltration in female oligometastatic breast cancer patients.MethodsWe retrospectively analyzed the clinicopathological data of oligometastatic breast cancer (OMBC) patients diagnosed between June 2000 and January 2020. Immune markers were quantified by immunohistochemistry on FFPE tissues in paired normal breast tissues, primary breast cancers and oligometastatic lesions. Survival analyses were performed using the Kaplan-Meier curves and Cox-proportional hazards model.ResultsA total of 95 female OMBC patients visited Sun Yat-sen University Cancer Center between June 2000 and January 2020, and 33 of them had matched normal breast tissues, primary cancers and oligometastatic lesions and were reviewed in immune infiltration analysis. CD8 of primary tumors had a higher expression than that in matched normal tissues. The expressions of CD8 and FOXP3 were higher in the primary sites than that in the oligometastatic lesions. CD3, CD4 and CD8 were significantly lower in the intratumoral regions than that in the peritumoral regions both in primary and oligometastatic lesions. Notably, the high percentage of CD3 in the intratumoral oligometastatic lesions predicted the longer PFS and OS, and higher CD4 in the same lesions also predicted a better OS. There was obviously positive correlation between CD4/CD3 and Ki-67 in primary cancers and negative correlation between CD4/CD3 and ER in oligometastatic sites.ConclusionWe explored immune distribution and evolution in time and space in OMBC to provide new understandings for biological behaviors of this disease and further divided patients in different prognosis.</p

Additional file 1 of EGFR T790M relative mutation purity predicts osimertinib treatment efficacy in non-small cell lung cancer patients

Additional file 1: Table S1. Gene lists of targeted next-generation sequencing panels our study involved

Additional file 1: of The correlations of tumor mutational burden among single-region tissue, multi-region tissues and blood in non-small cell lung cancer

Table S1. Clinical characteristics of the enrolled 32 NSCLC patients. Table S2. List of target regions of the pan-cancer 1021-gene panel. (DOCX 43 kb

Additional file 9: of Intratumor heterogeneity comparison among different subtypes of non-small-cell lung cancer through multi-region tissue and matched ctDNA sequencing

Figure S6. Driver dominance score. Driver dominance score measures driver self-sufficiency for each driver gene calculated across 32 patients. It is plotted against the fraction of patients carrying the mutated driver. (PDF 179 kb

Additional file 3 of The correlations of tumor mutational burden among single-region tissue, multi-region tissues and blood in non-small cell lung cancer

Figure S1. The correlations of TMB value between panel sequencing and WES in published databases. Figure S2. The comparison of multi-region tTMB among different NSCLC subtypes. Figure S3. The comparisons and overlaps of tumor-derived mutational profiles among tumor tissues in each region and the corresponding ctDNA. (PDF 1439 kb

Additional file 2: of The correlations of tumor mutational burden among single-region tissue, multi-region tissues and blood in non-small cell lung cancer

Supplementary Methods. (DOCX 24 kb

Additional file 6: of Intratumor heterogeneity comparison among different subtypes of non-small-cell lung cancer through multi-region tissue and matched ctDNA sequencing

Figure S3. The landscape of genomic alterations in enrolled non-small cell lung cancer patients. Integrated genomic data for 181 regions from 32 NSCLC patients. Overall number of mutations, as well as pathological type and typical mutant driver for each sample, were shown at the top. The group at the top and the patient No. at the bottom indicate contiguous regions from each patient. The percentage of NSCLC regions with an alteration was shown on the left in the order of the mutated genes as listed to the right of the panel. (PDF 276 kb

Additional file 7: of Intratumor heterogeneity comparison among different subtypes of non-small-cell lung cancer through multi-region tissue and matched ctDNA sequencing

Figure S4. The comparison of commonly mutated genes in non-small cell lung cancer among three different cohorts. (PDF 59 kb