Evidence map›Paper›PMID 26755347›Full record

ArticleScientific reports2016

Systematic Analysis of Sex-Linked Molecular Alterations and Therapies in Cancer.

Jonathan Ma, Sadhika Malladi, Andrew H Beck

Open access · goldAbstract read
In one paragraph

Article in Scientific reports, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.

0numbers the graph read from it
0cells of the map it votes in
16citing papers in PubMed
3.3field-weighted citation impact, top 8% of its field
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

16 citing papers in PubMed, 27 citations in OpenAlex.

  1. Review
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  4. Paternal impact on the developmental programming of sexual dimorphism.Frontiers in cell and developmental biology · 2024
    Review
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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

3 authors at 2 institutions in 1 country.

Jonathan MaThe Harker School, CA 95128.
Sadhika MalladiThe Harker School, CA 95128.
Andrew H BeckDepartment of Pathology, Beth Israel Deaconess Medical Center and Harvard Medical School, MA.
Beth Israel Deaconess Medical Center · USHarvard University · US

Funding

INFORMATICS METHODS AND MODELS FOR COMPUTATIONAL PATHOLOGYK22LM011931 · NLM · BETH ISRAEL DEACONESS MEDICAL CENTER · PI BECK, ANDREW H · 2014 to 2016
$476k
NLM NIH HHS K22 LM011931NLM NIH HHS K22LM011931
6 · The paper itself

Abstract

Though patient sex influences response to cancer treatments, little is known of the molecular causes, and cancer therapies are generally given irrespective of patient sex. We assessed transcriptomic differences in tumors from men and women spanning 17 cancer types, and we assessed differential expression between tumor and normal samples stratified by sex across 7 cancers. We used the LincsCloud platform to perform Connectivity Map analyses to link transcriptomic signatures identified in male and female tumors with chemical and genetic perturbagens, and we performed permutation testing to identify perturbagens that showed significantly differential connectivity with male and female tumors. Our analyses predicted that females are sensitive and males are resistant to tamoxifen treatment of lung adenocarcinoma, a finding which is consistent with known male-female differences in lung cancer. We made several novel predictions, including that CDK1 and PTPN1 knockdown would be more effective in males with hepatocellular carcinoma, and SMAD3 and HSPA4 knockdown would be more effective in females with head and neck squamous cell carcinoma. Our results provide a new resource for researchers studying male-female biological and treatment response differences in human cancer. The complete results of our analyses are provided at the website accompanying this manuscript (http://becklab.github.io/SexLinked).

Indexed as

Sex CharacteristicsFemaleGene Expression Regulation, NeoplasticHumansMaleNeoplasmsRNA, MessengerTranscriptomeRNA, Messenger

Identifiers

PMID26755347
PMCPMC4709570
OpenAlexW2232665699

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.