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Molecular Technologies in Gynecologic Oncology

2015· article· en· W2226333405 on OpenAlexvenueno aff
Ciro Comparetto, Franco Borruto

Bibliographic record

VenueJournal of cancer research updates · 2015
Typearticle
Languageen
FieldMedicine
TopicOvarian cancer diagnosis and treatment
Canadian institutionsnot available
Fundersnot available
KeywordsCancerOvarian cancerMedicineMolecular pathologyMolecular diagnosticsOncologyInternal medicineGeneBiologyPathologyBioinformaticsGenetics

Abstract

fetched live from OpenAlex

In recent years, the application of molecular biological techniques to the diagnosis and treatment of cancer has proved successful. In this kind of pathologies, molecular diagnosis is of fundamental importance as it allows identification at a pre-symptomatic stage, and then in the early phase, of the subjects in which cancer disease is developing. Molecular diagnosis of tumors by deoxy-ribonucleic acid (DNA) analysis is conducted on biological samples such as urine, feces, sputum, vaginal swab, and blood, searching and identifying in the various samples for the presence of cell carriers of an altered genetic information. The sensitivity of this kind of analysis is so high as to be very reliable even in the presence in the sample of a few tumor cells, level not reachable through the traditional “tumor markers”. The achievement of a facilitated early diagnosis of the tumor and, consequently, through the organization of specific therapeutic interventions, the prevention of the invasiveness of the pathology, allow to insert this kind of analysis among the most important investigations in the field of cancer prevention. Molecular oncology examinations have targeted the mutational study of the most involved genes in the onset of hereditary and/or family cancers such as breast, ovary, colon, melanoma, stomach, thyroid, etc. In addition, given the growing focus on the molecular mechanisms underlying the individual response to conventional chemotherapeutic drugs and molecular targeted agents responsible for drug resistance, pharmacogenetics exams have been added to those of molecular oncology. Some genes, when altered and/or mutated, can cause the development of tumors. In some types of cancer, the mutation may affect only somatic cells: in this case, the development will manifest itself only in the subject carrier of the mutation. Otherwise, if the mutation affects germ cells genes, it may occur the possibility to convey to children a susceptibility to the development of tumors. In fact, a significant proportion of cancers are hereditary. For example, it is estimated that about 7% of breast cancers, 10% of ovarian cancers, and about 5-10% of colorectal cancers, are caused by recurrent mutations at specific genes level. The early detection of cancer, with the ability to identify individuals at risk of developing the disease, is now the best way to reduce mortality from it. Determining whether a person has a mutation in a gene involved in neoplastic transformation that predisposes to the development of cancer (susceptibility or genetic predisposition) can significantly decrease its incidence and mortality. For example, as a result of in-depth studies of families at risk, it has been estimated that women who have inherited mutations in breast cancer genes (BRCA1 or BRCA2) are likely to develop breast cancer in 87% of cases, compared with 10% of non-bearers. This probability falls to 44-60% in the case of ovarian cancer, compared with 1% probability of not carriers. In this area, basic research has been developed with the aim of contributing to the study of the molecular mechanisms of oncogenesis, which generally has multistage character, with an initial immortalization and cell transformation and subsequent tumor progression. In this regard, studies at the molecular and functional level have been focused on models of different types of cancer, e.g. melanoma. In parallel, it has been studied the possible oncogenetic role of certain families of genes that have a functional role in embryogenesis, and in general in cell proliferation/differentiation, e.g. homeotic (HOX) genes. The gene expression profiles of purified cancer cells can be evaluated by microarray technique, comparing them with those of normal cells: comparative analysis, based on specific software, allows the identification of genes selectively modulated in the genetic program of tumor cells, in particular of genes specifically involved in the onset and progression of tumors. The modern goal of cancer therapy is to eliminate the disease by minimizing trauma and paying attention to the quality of life (QOL). With the passing of time, there has been a change of therapeutic paradigms and we have gone from the objective of maximum tolerable treatment to that of minimum effective treatment. This clinical imperative has its foundation in the quick transfer of biological knowledges to the care, integrating molecular informations with the development of new treatment methods. Especially for a delicate operation, even psychologically, such as that for breast cancer. In this setting, we have focused particularly on the technique of sentinel lymph node, demonstrating the possibility to avoid the treatment of the axilla in patients at low risk of recurrence. The term “molecular targeted therapy” is used to refer to agents that target specific pathways activated in the processes of growth, survival, invasion, and metastasis of cancer cells and in tumor neo-angiogenesis. The large and perhaps excessive optimism, caused by the gradual deepening of the knowledges of these mechanisms, has received a further boost by the arrival on the therapeutic scene of imatinib and other drugs belonging to the class of targeted biomolecular agents, including some monoclonal antibodies (McAb) such as trastuzumab, rituximab, cetuximab, and bevacizumab, and some small molecules, already entered clinical practice. But the question we must ask is whether that enthusiasm is justified and supported by scientifically strong and clinically proven data. The difficulties encountered in the research and development of new truly effective molecules and the disappointing results obtained in the early life of some of these agents and, not least, the high costs of treatments must lead to greater caution. The medical oncologist has the inescapable duty to possess sufficient culture to be able to properly use these new therapies in his diagnosis and treatment decision-making.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.583
Threshold uncertainty score0.400

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.128
GPT teacher head0.484
Teacher spread0.356 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
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".

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Citations0
Published2015
Admission routes1
Has abstractyes

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