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Hyperglycosylated hCG Drives Malignancy in Most or All Human Cancers: Tying All Research Together

2018· article· en· W2790182102 on OpenAlexvenueno aff
Laurence A. Cole

Bibliographic record

VenueJournal of Analytical Oncology · 2018
Typearticle
Languageen
FieldMedicine
TopicGrowth Hormone and Insulin-like Growth Factors
Canadian institutionsnot available
Fundersnot available
KeywordsMalignancyCancerOvarian cancerEndocrinologyBiologyCancer cellApoptosisAntibodyInternal medicineCancer researchMedicineImmunologyGenetics

Abstract

fetched live from OpenAlex

Objectives: Two forms of hCG are produced, the hormone hCG binding a luteinizing hormone/hCG joint receptor and the autocrine hyperglycosylated hCG binding a TGF-ß receptor. In pregnancy, hyperglycosylated hCG drives placental cell growth and invasion in implantation of pregnancy. It also blocks apoptosis. Human cancer cells steal the hCG ß-subunit gene and use hyperglycosylated hCG and its ß-subunit to drive malignancy. Here we examine research into hyperglycosylated hCG and its ß-subunit, and show that these molecules drive malignancy in most or possibly all human cancers. Methods: Mouse monoclonal antibody B152was raised against intact hyperglycosylated hCG, batch C5. The antibody binds hyperglycosylated hCG and its ß-subunit but does not bind the hormone hCG or its subunits. Total hCG was measured using the Siemens Immulite hCG assay, hyperglycosylated hCG and its ß-subunit were measured using the antibody B152 assay. Results: Eight independent center show that the hCG ß-subunit produced by cancers promotes malignancy, enhances cancer cell growth, cancer cell invasion and blockage of apoptosis in cancers. A study of 42 choriocarcinoma cases shows that percentage hyperglycosylated hCG exactly correlates with weekly doubling rate of cancer. It is concluded that hyperglycosylated hCG drive malignancy in this cancer. In a study with 7 separate cancers it is shown that increasing concentrations of hyperglycosylated hCG enhance all cancers. Increasing concentration of monoclonal antibody B152. Hyperglycosylated hCG and its ß-subunit drives cancer growth, cancer invasion and blocks apoptosis in cancer cells. Antibody B152 suppressed cancer cell growth creating a non-malignant-like state (no growth, no invasion), with no cancer growth over a starting 70% confluency. Conclusions: Choriocarcinoma is an example of cancer driven in malignancy by hyperglycosylated hCG, cancer aggression (weekly doubling rate) exactly correlating with percent hyperglycosylated hCG. In examining cancers, antibody B152 suppresses malignancy totally halting cancer growth in 7 of 7 cancer. This confirms that only the antigens, hyperglycosylated hCG and its ß-subunit drives malignancy in cancer cases.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.169
GPT teacher head0.465
Teacher spread0.296 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations5
Published2018
Admission routes1
Has abstractyes

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