Evidence map›Paper›PMID 41239147›Full record

ReviewDiscover oncology2025

Immunotherapeutics in metastatic cancer management.

Manisha Shukla, Poorna Shri, Sunil Kumar Mahobiya, Rohit Kumar Vishwakarma

Abstract readReview
In one paragraph

Review in Discover oncology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Manisha ShuklaDepartment of Biotechnology, Pandit Shambhunath Shukla University, Shahdol, Madhya Pradesh, India. shuklamumaneesha@gmail.com.
Poorna ShriGanesh Shankar Vidyarthi Memorial Medical College, Kanpur, Uttar Pradesh, India.
Sunil Kumar MahobiyaDepartment of Biotechnology, Pandit Shambhunath Shukla University, Shahdol, Madhya Pradesh, India.
Rohit Kumar VishwakarmaDepartment of Biotechnology, Pandit Shambhunath Shukla University, Shahdol, Madhya Pradesh, India.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Metastatic cancer remains the leading cause of cancer-related mortality, largely owing to the limitations of conventional treatments such as chemotherapy, radiotherapy, and targeted agents that are challenged by tumor heterogeneity, acquired resistance, and systemic toxicity. In contrast, immunotherapy has emerged as a transformative modality, harnessing the power of the immune system to selectively target and eradicate tumor cells. This review systematically examines key immunotherapeutic strategies ranging from immune checkpoint inhibitors (ICIs) and monoclonal antibodies to cancer vaccines, oncolytic viruses, and adoptive cell therapies (such as CAR-T and TCR-engineered T cells). Of particular interest are personalized approaches, including neoantigen-based vaccines and tumor-infiltrating lymphocyte (TIL) therapies, which hold promise for tailored treatment but also present significant logistical and translational challenges. Central to therapeutic outcomes are factors like immune resistance, the suppressive tumor microenvironment, and the identification of predictive biomarkers including PD-L1 expression and tumor mutational burden (TMB) that can guide patient selection and efficacy. As the field progresses, future breakthroughs will hinge on deepening our understanding of metastasis immunobiology, refining biomarker-driven precision approaches, and developing novel immunological targets and delivery platforms to improve outcomes and accessibility.

Indexed as

Cancer vaccinesCAR-T cellsImmune checkpoint inhibitorsImmunotherapyMetastatic cancerTumor microenvironment

Identifiers

PMID41239147
PMCPMC12618787

What OpenQuestion holds

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LicenceCC BY-NC-ND
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Registered trials

None linked

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.