Pan-cancer integrative histology-genomic analysis via multimodal deep learning.

The rapidly emerging field of computational pathology has demonstrated promise in developing objective prognostic models from histology images. However, most prognostic models are either based on histology or genomics alone and do not address how these data sources can be integrated to develop joint image-omic prognostic models. Additionally, identifying explainable morphological and molecular descriptors from these models that govern such prognosis is of interest.

Tumor fraction-guided cell-free DNA profiling in metastatic solid tumor patients.

Background: Cell-free DNA (cfDNA) profiling is increasingly used to guide cancer care, yet mutations are not always identified. The ability to detect somatic mutations in plasma depends on both assay sensitivity and the fraction of circulating DNA in plasma that is tumor-derived (i.e.

AI-based pathology predicts origins for cancers of unknown primary.

Cancer of unknown primary (CUP) origin is an enigmatic group of diagnoses in which the primary anatomical site of tumour origin cannot be determined. This poses a considerable challenge, as modern therapeutics are predominantly specific to the primary tumour. Recent research has focused on using genomics and transcriptomics to identify the origin of a tumour.

Development of Genome-Derived Tumor Type Prediction to Inform Clinical Cancer Care.

Importance: Diagnosing the site of origin for cancer is a pillar of disease classification that has directed clinical care for more than a century. Even in an era of precision oncologic practice, in which treatment is increasingly informed by the presence or absence of mutant genes responsible for cancer growth and progression, tumor origin remains a critical factor in tumor biologic characteristics and therapeutic sensitivity.

Objective: To evaluate whether data derived from routine clinical DNA sequencing of tumors could complement conventional approaches to enable improved diagnostic accuracy.

A rectal cancer organoid platform to study individual responses to chemoradiation.

Rectal cancer (RC) is a challenging disease to treat that requires chemotherapy, radiation and surgery to optimize outcomes for individual patients. No accurate model of RC exists to answer fundamental research questions relevant to patients. We established a biorepository of 65 patient-derived RC organoid cultures (tumoroids) from patients with primary, metastatic or recurrent disease.

Multicenter Prospective Phase II Trial of Neoadjuvant Dose-Dense Gemcitabine Plus Cisplatin in Patients With Muscle-Invasive Bladder Cancer.

Purpose Neoadjuvant chemotherapy followed by radical cystectomy (RC) is a standard of care for the management of muscle-invasive bladder cancer (MIBC). Dose-dense cisplatin-based regimens have yielded favorable outcomes compared with standard-dose chemotherapy, yet the optimal neoadjuvant regimen remains undefined. We assessed the efficacy and tolerability of six cycles of neoadjuvant dose-dense gemcitabine and cisplatin (ddGC) in patients with MIBC.

Cytokine profile in Egyptian hepatitis C virus genotype-4 in relation to liver disease progression.

Aim: To observe the imbalance between T helper cell Th1 and Th2 cytokines in several chronic hepatitis disease at different stages of disease progression.

Methods: We measured the cytokine levels of Th1 (IL-2 and IL-2R), Th2 (IL-10) and the pro-inflammatory cytokines (IL-6 and IL-6R and TNF and TNF-RI and II) by the ELISA technique in the sera of 33 hepatocellular carcinoma (HCC) patients and 20 chronic liver disease (CLD) patients. In addition, 20 asymptomatic hepatitis C virus carriers and 20 healthy subjects negative for hepatitis C virus(HCV) markers served as controls.