The p12 protein is a cleavage product of the Gag precursor of the murine leukemia virus (MLV). Specific mutations in p12 have been described that affect early stages of infection, rendering the virus replication-defective. Such mutants showed normal generation of genomic DNA but no formation of circular forms, which are markers of nuclear entry by the viral DNA. This suggested that p12 may function in early stages of infection but the precise mechanism of p12 action is not known. To address the function and follow the intracellular localization of the wt p12 protein, we generated tagged p12 proteins in the context of a replication-competent virus, which allowed for the detection of p12 at early stages of infection by immunofluorescence. p12 was found to be distributed to discrete puncta, indicative of macromolecular complexes. These complexes were localized to the cytoplasm early after infection, and thereafter accumulated adjacent to mitotic chromosomes. This chromosomal accumulation was impaired for p12 proteins with a mutation that rendered the virus integration-defective. Immunofluorescence demonstrated that intracellular p12 complexes co-localized with capsid, a known constituent of the MLV pre-integration complex (PIC), and immunofluorescence combined with fluorescent in situ hybridization (FISH) revealed co-localization of the p12 proteins with the incoming reverse transcribed viral DNA. Interactions of p12 with the capsid and with the viral DNA were also demonstrated by co-immunoprecipitation. These results imply that p12 proteins are components of the MLV PIC. Furthermore, a large excess of wt PICs did not rescue the defect in integration of PICs derived from mutant p12 particles, demonstrating that p12 exerts its function as part of this complex. Altogether, these results imply that p12 proteins are constituent of the MLV PIC and function in directing the PIC from the cytoplasm towards integration.

Precision oncology is gradually advancing into mainstream clinical practice, demonstrating significant survival benefits. However, eligibility and response rates remain limited in many cases, calling for better predictive biomarkers.

Murine leukemia viruses (MLVs) naturally infect unsynchronized T and B lymphocytes, thus, the incoming virus encounters both interphase and mitotic cells. While it is well accepted that MLV requires cell division to complete its replication cycle, it is not known if ab initio infection of mitotic cells can result in productive infection. This question is highly relevant since the milieu of mitotic cells is markedly different from this of interphase cells; e.g. lacking radial microtubule network and intact nuclear envelope. To follow MLV infection in mitotic and interphase cells in real-time, we employed our recently developed infectious MLV particles with labeled cores, cellular models expressing fluorescence markers of different intracellular compartments and protocols for reversible mitotic arrest of MLV-susceptible cells.

The murine leukaemia virus (MLV) gag gene encodes a small protein called p12 that is essential for the early steps of viral replication. The N- and C-terminal regions of p12 are sequentially acting domains, both required for p12 function. Defects in the C-terminal domain can be overcome by introducing a chromatin binding motif into the protein. However, the function of the N-terminal domain remains unknown. Here, we undertook a detailed analysis of the effects of p12 mutation on incoming viral cores. We found that both reverse transcription complexes and isolated mature cores from N-terminal p12 mutants have altered capsid complexes compared to wild type virions. Electron microscopy revealed that mature N-terminal p12 mutant cores have different morphologies, although immature cores appear normal. Moreover, in immunofluorescent studies, both p12 and capsid proteins were lost rapidly from N-terminal p12 mutant viral cores after entry into target cells. Importantly, we determined that p12 binds directly to the MLV capsid lattice. However, we could not detect binding of an N-terminally altered p12 to capsid. Altogether, our data imply that p12 stabilises the mature MLV core, preventing premature loss of capsid, and that this is mediated by direct binding of p12 to the capsid shell. In this manner, p12 is also retained in the pre-integration complex where it facilitates tethering to mitotic chromosomes. These data also explain our previous observations that modifications to the N-terminus of p12 alter the ability of particles to abrogate restriction by TRIM5alpha and Fv1, factors that recognise viral capsid lattices.

The p12 protein of the murine leukemia virus (MLV) is a constituent of the pre-integration complex (PIC) but its function in this complex remains unknown. We developed an imaging system to monitor MLV PIC trafficking in live cells. This allowed the visualization of PIC docking to mitotic chromosomes and its release upon exit from mitosis. Docking occurred concomitantly with nuclear envelope breakdown and was impaired for PICs of viruses with lethal p12 mutations. Insertion of a heterologous chromatin binding module into p12 of one of these mutants restored PICs attachment to the chromosomes and partially rescued virus replication. Capsid dissociated from wild type PICs in mitotic cells but remained associated with PICs harboring tethering-negative p12 mutants. Altogether, these results explain, in part, MLV restriction to dividing cells and reveal a role for p12 as a factor that tethers MLV PIC to mitotic chromosomes.

Advances in artificial intelligence have paved the way for leveraging hematoxylin and eosin (H&E)-stained tumor slides for precision oncology. We present ENLIGHT-DeepPT, an approach for predicting response to multiple targeted and immunotherapies from H&E-slides. In difference from existing approaches that aim to predict treatment response directly from the slides, ENLIGHT-DeepPT is an indirect two-step approach consisting of (1) DeepPT, a new deep-learning framework that predicts genome-wide tumor mRNA expression from slides, and (2) ENLIGHT, which predicts response based on the DeepPT inferred expression values. DeepPT successfully predicts transcriptomics in all 16 TCGA cohorts tested and generalizes well to two independent datasets. Our key contribution is showing that ENLIGHT-DeepPT successfully predicts true responders in five independent patients' cohorts involving four different treatments spanning six cancer types with an overall odds ratio of 2.44, increasing the baseline response rate by 43.47% among predicted responders, without the need for any treatment data for training. Furthermore, its prediction accuracy on these datasets is comparable to a supervised approach predicting the response directly from the images, which needs to be trained and tested on the same cohort. ENLIGHT-DeepPT future application could provide clinicians with rapid treatment recommendations to an array of different therapies and importantly, may contribute to advancing precision oncology in developing countries.