pT3a renal cell carcinoma (RCC) encompasses three different types of progression features leading to persistent debate on prognostic heterogeneity and the need for reclassification. Data of 1606 patients with pT3aN0/xM0 RCC was analyzed according to the site of invasion (perinephric fat (PFI), sinus fat (SFI), renal vein (RVI), PFI and SFI without RVI (PFI + SFI), and both fat and vein (RVI + FI)) using Kaplan-Meier and Cox proportional hazards methods. RNA sequencing was performed on tumor samples from 19 SFI and 14 RVI patients to identify differentially expressed genes and pathway enrichments. Five-year DFS were 76%, 68.5%, 62.4%, 63.9%, and 50.1% for SFI, PFI, PFI + SFI, RVI and RVI + FI groups, respectively (p < 0.001). Vein invasion tumors demonstrating consistently poorer survival on size-stratified analysis. Site of invasion was an independent prognostic factor. Transcriptomic profiling revealed that SFI tumors were enriched for epithelial-mesenchymal transition, KRAS signaling, and extracellular matrix reprogramming, whereas RVI tumors exhibited hypoxia, oxidative phosphorylation, and DNA repair pathway activation. In T3a RCC, site of invasion was an independent prognosticator of survival regardless of tumor size. SFI and RVI tumors exhibited distinct genomic and pathway profiles suggesting an intrinsically disparate competencies directing the tumors to adopt different invasion mechanisms.

Existing epidemiological evidence regarding the potential role of (poly)phenol intake in lymphoma development is limited. We investigated the associations between the intake of total and individual classes and subclasses of (poly)phenols and the risk of lymphoma, including main frequent subtypes in the EPIC cohort using multivariable-adjusted Cox proportional hazards models. During a mean 14-year follow-up (time frame: from 1990-1994 to 2008-2013), 2394 incident lymphoma cases were diagnosed from a total of 367,463 individuals. No significant associations were observed between total intakes of (poly)phenols, flavonoids, and phenolic acids and overall lymphoma risk. Total (poly)phenols, phenolic acid and hydroxycinnamic acid intakes were positively associated with Hodgkin lymphoma (HL) risk [HRlog2 = 2.56 (95% confidence interval: 1.27-5.16); 1.81 (1.14-2.87); and 1.48 (1.03-2.12), respectively]. Conversely, isoflavone intakes was inversely associated with risk of overall lymphoma [HRlog2 = 0.96 (0.93-0.99)], and non-Hodgkin lymphoma [HRlog2 = 0.95 (0.92-0.99)] and mature B-cell lymphoma [HRlog2 = 0.96 (0.92-0.99)], and flavone intakes with risk of multiple myeloma/plasma cell neoplasm [HRlog2 = 0.75 (0.60-0.95)]. Our findings suggest that isoflavone intakes may reduce the risk of overall lymphoma and specific lymphoma subtypes, while phenolic acids, particularly hydroxycinnamic acids might increase the risk of HL.

Complement factors regulate tumour immunity in the tumour microenvironment (TME). We investigated the functions of complement 5a (C5a) and its receptors, C5aR1 and C5aR2, in forming the C5a-C5aR1 and C5a-C5aR2 signaling axes in the immune TME of pancreatic ductal adenocarcinoma (PDAC). C5a, C5aR1 and C5aR2 were assessed in cancer cell cytoplasmic (c-) and stromal (s-) expressions in resected PDAC tissues. In vitro assays were conducted to examine endogenous C5aR1 functions in PDAC cells, and orthotopic transplantation was performed in a preclinical study. In immunohistochemistry, High C5a-C5aR1 c-axis was correlated with poor prognosis and High C5a-C5aR1 s-axis was associated with a decrease in CD8+ T cells and an increase in CD11b+ MDSCs. C5aR1 knockdown and CCX168, the specific C5aR1 inhibitor, impaired proliferation and the activation of the PI3K/mTOR pathway, and enhanced gemcitabine sensitivity by increasing apoptosis. The combination of CCX168 and gemcitabine/nab-paclitaxel demonstrated a significant reduction in tumour volume. The number of CD8+ T cells was significantly increased in CCX168-treated groups, whereas CCX168 treatment resulted in a decrease in MDSCs. The C5a-C5aR1 axis may exert a tumour-promoting effect on the TME in PDAC. CCX168 appears to modulate antitumour immunity, thereby warranting future complement-based immunomodulation therapies for PDAC.

Routine histopathology cannot distinguish between clinically diverse luminal A and B breast cancer subtypes (LBCS), often requiring ancillary testing. Mueller matrix polarimetry (MMP) offers a promising approach by analysing polarised light interactions with complex breast tissues. This study explores the efficacy of using MMP for luminal subtype differentiation. We analysed 30 polarimetric and 7 clinical parameters from 116 unstained breast core biopsies, LBCS classified using the BluePrint® molecular assay. These features were used to train various machine learning models: logistic regression, linear discriminant analysis, support vector machine, random forest, and XGBoost to distinguish luminal subtypes. Receiver operating characteristic curve (ROC) analysis was used to each to assess diagnostic performance using area under the curve, accuracy, sensitivity, and specificity. Using the top six most prognostic polarimetric (three) and clinical (three) biomarkers ranked by feature importance, the best-performing random forest model achieved an accuracy of 81% (area under ROC = 86%), with both sensitivity and specificity at 75% on an unseen test set, indicating moderately promising, clinically informative performance. MMP, particularly its selected Mueller matrix elements, combined with clinical biomarkers show promise in distinguishing LBCS as validated against BluePrint®. By detecting subtle differences in tissue morphology, this approach may enhance breast cancer prognosis and help guide treatment decisions.

Persistent HPV infection causes cervical cancer, but most infections are transient. Triage methods identify high-risk women needing further evaluation or treatment. We assessed short-term repeat HPV testing as an alternative triage option. In ESTAMPA, women aged 30-64 years were screened with HPV testing (HC2 or Cobas) and cytology. Screen positives were referred to colposcopy approximately two months after screening, where cervical samples were collected again for repeat HPV testing. We evaluated the performance of repeat HPV for CIN3+ among HPV-positive women and explored its combination with limited HPV genotyping (HPV16/18). Among 5390 HPV-positive women (including 629 CIN3 cases and 53 cancers), 61% retested positive at~2 months (median: 1.8, interquartile range: 1.2-2.8). Repeat HPV sensitivity for CIN3+ was 81.5% (95% CI 77.2-85.2) for HC2 and 87.7% (83.7-90.8) for Cobas. Specificity was <50% with referral rates of 57.4% (55.7-59.0) and 68.2% (66.1-70.2) for HC2 and Cobas. HPV16/18 genotyping followed by repeat HPV among non-HPV16/18-positive women did not greatly improve performance. However, HPV16/18 positivity doubled the risk of CIN3+, supporting its combination with repeat HPV when available. Short-term repeat HPV testing could be a practical option for triaging HPV-positive women, either alone or in combination with limited HPV genotyping. ClinicalTrials.gov, NCT01881659.

Breast cancer distant metastasis is known to exhibit organotropism, with triple negative breast cancer (TNBC) subtypes also displaying organ-specific metastasis. The precise regulatory mechanisms governing this specificity remain unclear. Retrospective analysis of metastatic data from public databases was utilized to explore the organotropism of TNBC subtypes. Mouse models combined with single-cell sequencing and immunoprecipitation (CoIP) experiments were utilized to investigate the role and mechanism of androgen receptor (AR)onTNBC bone metastasis. Further analysis of the bone microenvironment combined with CUT&TAG sequencing and osteoclast differentiation experiments was performed to validate the effect of AR and c-Myc interaction on macrophage-osteoclast axis differentiation. Analysis revealed the luminal androgen receptor (LAR) TNBC subtype had significant bone metastasis propensity. Mouse models showedARactivation promoted LAR TNBC bone metastasis. Using single-cell sequencing, we discovered that c-Myc played a critical role in AR-mediated bone metastasis. Further investigation of the bone microenvironment showed that AR-c-Myc interaction promoted macrophage-osteoclast axis differentiation and macrophage activation via MMP13, ultimately increasing bone resorption. AR and c-Myc interaction induces macrophage differentiation into osteoclasts and promotes TNBC bone metastasis. These findings elucidate the mechanisms underlying bone metastasis in TNBC subtypes and inform potential interventions for TNBC bone metastasis.

Diagnosing AFP-negative hepatocellular carcinoma (HCC) is challenging. Autoantibodies to tumor-associated antigens have been extensively investigated as serum biomarkers. We employed serological proteome analysis and protein microarray to identify potential autoantibodies for HCC, followed by a two-center and two-independent-phase validation and evaluation using ELISA in patients with AFP-negative HCC (ANHCC). LASSO regression addressed multicollinearity among biomarkers. Four machine-learning methods developed diagnostic models for ANHCC. ROC analysis and various evaluation indicators were applied to assess the performance. Eight autoantibodies out of sixteen candidates, including Survivin, NPM1, GNAS, SRSF2, GNA11, PTCH1, GAPDH, and HSP90, were validated as superior biomarkers. The Logistic regression model was optimal for ANHCC, achieving an area under the ROC (AUC) of 0.883 in the training dataset and an AUC of 0.840 in the validation dataset. When tested on the entire HCC patient cohort, which included both ANHCC and AFP-positive patients (APHCC), with ANHCC accounting for 37.5%, the AUC reached 0.825, with a sensitivity of 66.4%, and a specificity of 84.2%. Combining this model with AFP improved efficacy, yielding an AUC of 0.945, an IDI of 23.1%, and an NRI of 21.1% compared to using AFP alone. The Logistic regression model demonstrates superior diagnostic performance for ANHCC. Integrating this model with AFP enhances the entire HCC diagnosis.