Identification of surrogate biomarkers for the replacement histopathological growth pattern in colorectal cancer liver metastasis
Notice bibliographique
Résumé
Introduction: Colorectal cancer (CRC) is the third most common cancer in both males and females in North America. It is the second leading cause of cancer-related deaths due in large part to CRC liver metastasis (CRCLM), with which approximately 50% of patients will be diagnosed during the course of their disease. Three major histopathological growth patterns (HGP) have been identified in CRCLM, and evidence suggests that the tumour's predominant HGP has prognostic implications. Specifically, CRCLMs that present with the replacement growth pattern are resistant to anti-angiogenic therapy, which is frequently used alongside neoadjuvant chemotherapy for the treatment of metastatic CRC. The HGPs in CRCLM may have a promising role as predictive biomarkers of response to angiogenesis inhibitors, where no such marker has yet been validated. However, a CRCLM's growth pattern must be evaluated by a pathologist from resected tumour tissue, implying that preoperative treatment precedes HGP scoring. Therefore, surrogate molecular markers for the CRCLM HGPs that can be assessed prior to surgery would be instrumental in determining whether a patient may benefit from anti-angiogenic treatment. Objectives: It is hypothesized that there are products of differentially expressed genes (DEG) in replacement HGP CRCLMs that may serve as potential diagnostic biomarkers and/or targets for anti-metastatic therapy. The objective of this study is to characterize and compare the global gene expression profiles of chemonaïve CRCLMs presenting with the replacement or desmoplastic HGPs via RNA sequencing (RNA-Seq) and immunohistochemical staining. The secondary aim is to isolate extracellular vesicles (EV) from the plasma of CRCLM patients and verify whether they contain the gene products of select DEGs. Methods: RNA-Seq was performed using the total RNA extracted from liver metastases and adjacent normal liver tissues that had been resected from 18 patients with CRCLM who did not receive preoperative chemotherapy. Immunohistochemical staining of select DEGs identified from the RNA-Seq data, among other protein targets, was then performed on formalin-fixed, paraffin-embedded (FFPE) CRCLM samples. The visualization and analysis of immunohistochemistry results were done using the Aperio ImageScope software program. Lastly, EVs were isolated from patient plasma samples by differential centrifugation and subsequently lysed for protein detection via Western blot. Results: A gene expression signature comprised of genes whose transcription was upregulated in chemonaïve replacement HGP CRCLMs compared to chemonaïve desmoplastic HGP CRCLMs and normal liver tissues was generated. The protein levels of one of these genes, LOXL4, were found to be significantly elevated at the tumour-liver interface and in areas of inflammation in replacement HGP metastases. LOXL4 protein was also detectable in EVs isolated from the plasma of patients with CRCLM or benign liver disease, though the quantities were comparable between the growth patterns. Conclusion: Our study showed that the replacement and desmoplastic HGP CRCLMs have distinguishable gene expression profiles, with several genes related to the extracellular matrix and the immune system being upregulated in replacement HGP metastases. The expression levels of LOXL4 mRNA and protein were significantly elevated in replacement HGP CRCLMs relative to desmoplastic HGP CRCLMs, and LOXL4 protein is also detectable in EVs isolated from patient plasma. Therefore, LOXL4 may potentially serve as a surrogate biomarker for the replacement HGP in CRCLM.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».