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The risk of colorectal cancer (CRC) depends on environmental and genetic factors. Among environmental factors, an imbalance in the gut microbiota can increase CRC risk. Also, microbiota is influenced by host genetics. However, it is not known if germline variants influence CRC development by modulating microbiota composition. We investigated germline variants associated with the abundance of bacterial populations in the normal (non-involved) colorectal mucosa of 93 CRC patients and evaluated their possible role in disease. Using a multivariable linear regression, we assessed the association between germline variants identified by genome wide genotyping and bacteria abundances determined by 16S rRNA gene sequencing. We identified 37 germline variants associated with the abundance of the genera Bacteroides, Ruminococcus, Akkermansia, Faecalibacterium and Gemmiger and with alpha diversity. These variants are correlated with the expression of 58 genes involved in inflammatory responses, cell adhesion, apoptosis and barrier integrity. Genes and bacteria appear to be involved in the same processes. In fact, expression of the pro-inflammatory genes GAL, GSDMD and LY6H was correlated with the abundance of Bacteroides, which has pro-inflammatory properties; abundance of the anti-inflammatory genus Faecalibacterium correlated with expression of KAZN, with barrier-enhancing functions. Both the microbiota composition and local inflammation are regulated, at least partially, by the same germline variants. These variants may regulate the microenvironment in which bacteria grow and predispose to the development of cancer. Identification of these variants is the first step to identifying higher-risk individuals and proposing tailored preventive treatments that increase beneficial bacterial populations. [ABSTRACT FROM AUTHOR]

Simple Summary: Oropharyngeal squamous cell carcinoma (OPSCC) has one of the most rapidly increasing incidences of any cancer in high-income countries. The aim of this study is to test whether radiomic and blood-derived biomarkers are good candidates for refining the prognostic stratification in OPSCC. The results show that the integration of clinical, immunological, and computed tomography-derived features generally yields an improvement, regardless of the HPV status, in the prognostic stratification of OPSCC patients who are candidates for curative-intent radiotherapy. Specifically, we documented a significant role of the Lymphocyte-to-Monocyte Ratio (LMR) in this population, which has been scarcely investigated in OPSCC, as well as the detrimental effects of lymphopenia and anemia. Results are promising, and model performances compare favorably with available radiomic scores in the same setting. Further investigations on our findings are warranted to validate the results and include a more in-depth study of the prognostic role of the LMR in OPSCC. Future analyses of this dataset are planned to provide a more complete overview of the tumor-immune system interplay. Aims: To assess whether CT-based radiomics and blood-derived biomarkers could improve the prediction of overall survival (OS) and locoregional progression-free survival (LRPFS) in patients with oropharyngeal cancer (OPC) treated with curative-intent RT. Methods: Consecutive OPC patients with primary tumors treated between 2005 and 2021 were included. Analyzed clinical variables included gender, age, smoking history, staging, subsite, HPV status, and blood parameters (baseline hemoglobin levels, neutrophils, monocytes, and platelets, and derived measurements). Radiomic features were extracted from the gross tumor volumes (GTVs) of the primary tumor using pyradiomics. Outcomes of interest were LRPFS and OS. Following feature selection, a radiomic score (RS) was calculated for each patient. Significant variables, along with age and gender, were included in multivariable analysis, and models were retained if statistically significant. The models' performance was compared by the C-index. Results: One hundred and five patients, predominately male (71%), were included in the analysis. The median age was 59 (IQR: 52–66) years, and stage IVA was the most represented (70%). HPV status was positive in 63 patients, negative in 7, and missing in 35 patients. The median OS follow-up was 6.3 (IQR: 5.5–7.9) years. A statistically significant association between low Hb levels and poorer LRPFS in the HPV-positive subgroup (p = 0.038) was identified. The calculation of the RS successfully stratified patients according to both OS (log-rank p < 0.0001) and LRPFS (log-rank p = 0.0002). The C-index of the clinical and radiomic model resulted in 0.82 [CI: 0.80–0.84] for OS and 0.77 [CI: 0.75–0.79] for LRPFS. Conclusions: Our results show that radiomics could provide clinically significant informative content in this scenario. The best performances were obtained by combining clinical and quantitative imaging variables, thus suggesting the potential of integrative modeling for outcome predictions in this setting of patients. [ABSTRACT FROM AUTHOR]

• Positive sentinel node biopsy (SLNB) after neoadjuvant therapy (NAST) is an issue. • Positive SLNB is associated with high rate of residual positive lymph nodes. • Positive SLNB after NAST warrants treatment of axilla (dissection/radiotherapy-RT) • Predictors of positive axilla lymph nodes distribution might help to tailor RT fields. To assess the rate of positive non-sentinel lymph nodes (non-SLNs) after neoadjuvant systemic therapy (NAST) in breast cancer (BC) following positive sentinel lymph node biopsy (SLNB). From institutional database, 265 consecutive patients receiving NAST for cT1-3, any N, M0 BC between 2001 and 2018 were identified. Patients presented clinically negative axilla before surgery and were candidate for SLNB. Following metastatic SLNB, completion axillary lymph node dissection (AxLND) was performed. Non-SLNs rate was investigated using multivariate (MV) logistic regression models. The distribution of non-SLNs across the axilla was observed. Positive non-SLNs were found in 62.3% of cases and showed no correlation with SLN metastasis size. At MV, statistically significant variables associated with non-SLNs were older age (p = 0.025), clinically positive lymph nodes (p = 0.002), SLN extracapsular extension (ECE, p = 0.001), and higher ratio of positive SLNs/total SLNs (p = 0.016). ECE and higher nodal ratio were independent predictors of III axillary level positivity. By categorizing patients in intermediate- and high-risk groups using the study variables, positive non-SLNs were found in the range of 23–56% across the three axillary levels, rates which did not support radiotherapy volume de-escalation. The III axillary level lower involvement (6.3%) was better identified with the RAPCHEM trial criteria based on the ypN status after AxLND. Involved non-SLNs rate following positive SLNB after NAST is nearly double the rate observed after primary surgery, supporting some intervention on the axilla. If AxLND is limited to I and II level, the involvement of the III level up to 31% of the cases seems to require some additional treatment, while the omission in selected cases needs further investigation. [ABSTRACT FROM AUTHOR]

Alterations in the gene expression of organs in contact with the environment may signal exposure to toxins. To identify genes in lung tissue whose expression levels are altered by cigarette smoking, we compared the transcriptomes of lung tissue between 118 ever smokers and 58 never smokers. In all cases, the tissue studied was non-involved lung tissue obtained at lobectomy from patients with lung adenocarcinoma. Of the 17,097 genes analyzed, 357 were differentially expressed between ever smokers and never smokers (FDR < 0.05), including 290 genes that were up-regulated and 67 down-regulated in ever smokers. For 85 genes, the absolute value of the fold change was ≥2. The gene with the smallest FDR was MYO1A (FDR = 6.9 × 10−4) while the gene with the largest difference between groups was FGG (fold change = 31.60). Overall, 100 of the genes identified in this study (38.6%) had previously been found to associate with smoking in at least one of four previously reported datasets of non-involved lung tissue. Seven genes (KMO, CD1A, SPINK5, TREM2, CYBB, DNASE2B, FGG) were differentially expressed between ever and never smokers in all five datasets, with concordant higher expression in ever smokers. Smoking-induced up-regulation of six of these genes was also observed in a transcription dataset from lung tissue of non-cancer patients. Among the three most significant gene networks, two are involved in immunity and inflammation and one in cell death. Overall, this study shows that the lung parenchyma transcriptome of smokers has altered gene expression and that these alterations are reproducible in different series of smokers across countries. Moreover, this study identified a seven-gene panel that reflects lung tissue exposure to cigarette smoke. [ABSTRACT FROM AUTHOR]