ReviewCancer metastasis reviews2024
Melanoma in people living with HIV: Immune landscape dynamics and the role of immuno- and antiviral therapies.
Review in Cancer metastasis reviews, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
5 citing papers in PubMed.
- Persistent NET states link lesion-related microbial signals to the cold tumor-related local restrictive environment: a context-dependent working model.Cell communication and signaling : CCS · 2026Review
- Population Analysis and Immunologic Landscape of Melanoma in People Living with HIV.Clinical cancer research : an official journal of the American Association for Cancer Research · 2026Article
- TIL cell therapy in HIV positive patient with metastatic melanoma: case report.Frontiers in oncology · 2026Article
- Multi-Component Analysis of Protein- and DNA-Coated Magnetic Nanoparticles Using Electrochemical Impedance Spectroscopy with Interdigitated Electrode Sensors.Bioengineering (Basel, Switzerland) · 2025Article
- Population analysis and immunologic landscape of melanoma in people living with HIV.bioRxiv : the preprint server for biology · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The intersection of HIV and melanoma presents a complex and unique challenge, marked by distinct patterns in incidence, mortality, and treatment response. Higher mortality rates among people with HIV who develop melanoma underscore an urgent need to identify the factors influencing these outcomes. Investigating immune system dynamics, the effects of anti-retroviral drugs, and the evolving landscape of cancer immunotherapy in this population holds promise for new insights, though significant uncertainties remain. Over the past 25 years, melanoma research has demonstrated that a robust immune response is critical for effective treatment. In the context of chronic HIV infection, viral reservoirs enable the virus to persist despite anti-retroviral therapy and foster dysregulated myeloid and T cell compartments. The resulting chronic inflammation weakens the immune system and damages tissues, potentially creating "cold" tumor microenvironments that are less responsive to therapy. In this challenging context, animal models become invaluable for uncovering underlying biological mechanisms. While these models do not fully replicate human HIV infection, they provide essential insights into critical questions and inform the development of tailored treatments for this patient population. Clinically, increasing trial participation and creating a centralized, accessible repository for HIV and cancer samples and data are vital. Achieving these goals requires institutions to address barriers to research participation among people with HIV, focusing on patient-centered initiatives that leverage biomedical research to improve their outcomes and extend their lives.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.