Polymorphism in Gag Gene Cleavage Sites of HIV-1 Non-B Subtype and Virological Outcome of a First-Line Lopinavir/Ritonavir Single Drug Regimen

Virological failure on a boosted-protease inhibitor (PI/r) first-line triple combination is usually not associated with the detection of resistance mutations in the protease gene. Thus, other resistance pathways are being investigated. First-line PI/r monotherapy is the best model to investigate in vivo if the presence of mutations in the cleavage sites (CS) of gag gene prior to any antiretroviral treatment might influence PI/r efficacy. 83 patients were assigned to initiate antiretroviral treatment with first-line lopinavir/r monotherapy in the randomised Monark trial. We compared baseline sequence of gag CS between patients harbouring B or non-B HIV-1 subtype, and between those who achieved viral suppression and those who experienced virological failure while on LPV/r monotherapy up to Week 96. Baseline sequence of gag CS was available for 82/83 isolates; 81/82 carried at least one substitution in gag CS compared to HXB2 sequence. At baseline, non-B subtype isolates were significantly more likely to harbour mutations in gag CS than B subtype isolates (p<0.0001). Twenty-three patients experienced virological failure while on lopinavir/r monotherapy. The presence of more than two substitutions in p2/NC site at baseline significantly predicted virological failure (p = 0.0479), non-B subtype isolates being more likely to harbour more than two substitutions in this specific site. In conclusion, gag cleavage site was highly polymorphic in antiretroviral-naive patients harbouring a non-B HIV-1 strain. We show that pre-therapy mutations in gag cleavage site sequence were significantly associated with the virological outcome of a first-line LPV/r single drug regimen in the Monark trial

A dualistic model of primary anal canal adenocarcinoma with distinct cellular origins, etiologies, inflammatory microenvironments and mutational signatures: implications for personalised medicine.

Primary adenocarcinoma of the anal canal is a rare and aggressive gastrointestinal disease with unclear pathogenesis. Because of its rarity, no clear clinical practice guideline has been defined and a targeted therapeutic armamentarium has yet to be developed. The present article aimed at addressing this information gap by in-depth characterising the anal glandular neoplasms at the histologic, immunologic, genomic and epidemiologic levels. In this multi-institutional study, we first examined the histological features displayed by each collected tumour (n = 74) and analysed their etiological relationship with human papillomavirus (HPV) infection. The intratumoural immune cell subsets (CD4, CD8, Foxp3), the expression of immune checkpoints (PD-1, PD-L1), the defect in mismatch repair proteins and the mutation analysis of multiple clinically relevant genes in the gastrointestinal cancer setting were also determined. Finally, the prognostic significance of each clinicopathological variable was assessed. Phenotypic analysis revealed two region-specific subtypes of anal canal adenocarcinoma. The significant differences in the HPV status, density of tumour-infiltrating lymphocytes, expression of immune checkpoints and mutational profile of several targetable genes further supported the separation of these latter neoplasms into two distinct entities. Importantly, anal gland/transitional-type cancers, which poorly respond to standard treatments, displayed less mutations in downstream effectors of the EGFR signalling pathway (i.e., KRAS and NRAS) and demonstrated a significantly higher expression of the immune inhibitory ligand-receptor pair PD-1/PD-L1 compared to their counterparts arising from the colorectal mucosa. Taken together, the findings reported in the present article reveal, for the first time, that glandular neoplasms of the anal canal arise by HPV-dependent or independent pathways. These etiological differences leads to both individual immune profiles and mutational landscapes that can be targeted for therapeutic benefits

Cancer Biomarker Discovery: The Entropic Hallmark

Background: It is a commonly accepted belief that cancer cells modify their transcriptional state during the progression of the disease. We propose that the progression of cancer cells towards malignant phenotypes can be efficiently tracked using high-throughput technologies that follow the gradual changes observed in the gene expression profiles by employing Shannon's mathematical theory of communication. Methods based on Information Theory can then quantify the divergence of cancer cells' transcriptional profiles from those of normally appearing cells of the originating tissues. The relevance of the proposed methods can be evaluated using microarray datasets available in the public domain but the method is in principle applicable to other high-throughput methods. Methodology/Principal Findings: Using melanoma and prostate cancer datasets we illustrate how it is possible to employ Shannon Entropy and the Jensen-Shannon divergence to trace the transcriptional changes progression of the disease. We establish how the variations of these two measures correlate with established biomarkers of cancer progression. The Information Theory measures allow us to identify novel biomarkers for both progressive and relatively more sudden transcriptional changes leading to malignant phenotypes. At the same time, the methodology was able to validate a large number of genes and processes that seem to be implicated in the progression of melanoma and prostate cancer. Conclusions/Significance: We thus present a quantitative guiding rule, a new unifying hallmark of cancer: the cancer cell's transcriptome changes lead to measurable observed transitions of Normalized Shannon Entropy values (as measured by high-throughput technologies). At the same time, tumor cells increment their divergence from the normal tissue profile increasing their disorder via creation of states that we might not directly measure. This unifying hallmark allows, via the the Jensen-Shannon divergence, to identify the arrow of time of the processes from the gene expression profiles, and helps to map the phenotypical and molecular hallmarks of specific cancer subtypes. The deep mathematical basis of the approach allows us to suggest that this principle is, hopefully, of general applicability for other diseases