# Modulation of Oncogenic NOTCH Signaling in Highly Aggressive Malignancies by Targeting the γ-Secretase Complex: A Systematic Review

**Authors:** Pablo Martínez-Gascueña, María-Luisa Nueda, Victoriano Baladrón

PMC · DOI: 10.3390/cells15050468 · 2026-03-05

## TL;DR

This review explores how targeting the NOTCH signaling pathway with γ-secretase inhibitors (GSIs) can help treat aggressive cancers, but highlights challenges like toxicity and the need for more specific therapies.

## Contribution

The paper systematically evaluates preclinical and clinical evidence for GSIs in multiple cancer types and proposes future strategies for improving their efficacy and specificity.

## Key findings

- GSIs show promise in preclinical models by enhancing chemotherapy and radiotherapy effects and overcoming resistance.
- Clinical trials with GSIs have shown limited success due to toxicity and non-selective inhibition of NOTCH signaling.
- Future approaches should focus on receptor-specific inhibitors and combination therapies to improve outcomes.

## Abstract

What are the main findings?
γ-secretase inhibitors (GSIs) and other alternative strategies demonstrate promising antitumor activity in vitro and in mouse xenograft models, potentiating the effects of chemotherapy and radiotherapy, and helping overcome therapy resistance and improve patient prognosis.Some GSIs may also exhibit dose- and time-dependent influences on the tumor’s oncogenic properties. However, despite encouraging preclinical findings, clinical trial results remain limited.

γ-secretase inhibitors (GSIs) and other alternative strategies demonstrate promising antitumor activity in vitro and in mouse xenograft models, potentiating the effects of chemotherapy and radiotherapy, and helping overcome therapy resistance and improve patient prognosis.

Some GSIs may also exhibit dose- and time-dependent influences on the tumor’s oncogenic properties. However, despite encouraging preclinical findings, clinical trial results remain limited.

What are the implications of the main findings?
The broad inhibition of the NOTCH pathway by GSIs can unintentionally suppress tumor-suppressive NOTCH receptors (such as NOTCH2 in certain breast cancer subtypes). Moreover, partial, or low-level pathway inhibition may paradoxically promote cellular proliferation, leading to unpredictable therapeutic outcomes. For these reasons, next-generation approaches should focus on developing receptor-specific GSIs or alternative NOTCH-targeting agents (e.g., DLK1/DLK2 modulators). The use of cell lines with artificially overactivated NOTCH signaling may not fully reflect the heterogeneity of human tumors, and GSIs may only target specific cellular subpopulations. In clinical settings, their application has been limited by significant toxicity and poor tolerability.Future research should further investigate microenvironment-driven mechanisms of drug resistance, including EMT, invasion, and stromal interactions. A deeper understanding of immune-evasion strategies could improve immunotherapy efficacy. In parallel, anti-angiogenic approaches should be prioritized as key therapeutic strategies. Advanced therapeutic modalities, such as CRISPR-based editing, CAR T-cell therapy, bispecific antibodies, and nanoparticle-mediated targeted delivery, may enhance treatment precision while reducing toxicity. Targeting cancer stem cells remains a central objective. Treatment optimization should incorporate patient stratification based on NOTCH receptor and ligand expression, pathway activation status, and immune antigen profiles. Emerging tools such as AI and big-data analytics will support the personalization of cancer therapies and should account for sex-specific biological differences to maximize therapeutic efficacy.

The broad inhibition of the NOTCH pathway by GSIs can unintentionally suppress tumor-suppressive NOTCH receptors (such as NOTCH2 in certain breast cancer subtypes). Moreover, partial, or low-level pathway inhibition may paradoxically promote cellular proliferation, leading to unpredictable therapeutic outcomes. For these reasons, next-generation approaches should focus on developing receptor-specific GSIs or alternative NOTCH-targeting agents (e.g., DLK1/DLK2 modulators). The use of cell lines with artificially overactivated NOTCH signaling may not fully reflect the heterogeneity of human tumors, and GSIs may only target specific cellular subpopulations. In clinical settings, their application has been limited by significant toxicity and poor tolerability.

Future research should further investigate microenvironment-driven mechanisms of drug resistance, including EMT, invasion, and stromal interactions. A deeper understanding of immune-evasion strategies could improve immunotherapy efficacy. In parallel, anti-angiogenic approaches should be prioritized as key therapeutic strategies. Advanced therapeutic modalities, such as CRISPR-based editing, CAR T-cell therapy, bispecific antibodies, and nanoparticle-mediated targeted delivery, may enhance treatment precision while reducing toxicity. Targeting cancer stem cells remains a central objective. Treatment optimization should incorporate patient stratification based on NOTCH receptor and ligand expression, pathway activation status, and immune antigen profiles. Emerging tools such as AI and big-data analytics will support the personalization of cancer therapies and should account for sex-specific biological differences to maximize therapeutic efficacy.

Background. NOTCH receptors play a pivotal role in carcinogenesis. Upon ligand binding, a cascade of proteolytic cleavages mediated by ADAM proteases and the γ-secretase complex activates the receptor, ultimately releasing the NOTCH intracellular domain (NICD). NICD translocates to the nucleus, where it regulates gene expression. This review mainly aims to evaluate γ-secretase inhibitors (GSIs) as anticancer agents in preclinical and clinical settings, with a focus on their ability to block tumor progression, target cancer stem cells, and overcome resistance to standard therapies. Methods. A systematic search was conducted in the ISI Web of Science, PubMed, and Scopus databases, following PRISMA guidelines. The review included preclinical in vitro and in vivo studies, as well as clinical trials, investigating GSIs, either as monotherapy or in combination with other treatments, in TNBC, metastatic melanoma, PDAC, gastric cancer, and NSCLC. Exclusion criteria included duplicates, non-English articles, studies published before 2010, studies on non-cancer conditions, research unrelated to NOTCH signaling, and studies outside the selected cancer types. Overall, 69 articles were included and categorized into the five types of cancer analyzed (20 on NSCLC, 22 on TNBC, 11 on metastatic melanoma, 7 on GC, and 9 on PDAC). Of these, 60 studies corresponded to preclinical research in the types of cancer, and 9 studies corresponded to clinical trials in the types of cancer except for GC. Two independent authors screened and extracted relevant data, with disagreements resolved by the corresponding author. Findings were synthesized qualitatively across cancer types under study. Results. This review summarizes therapeutic advances involving GSIs in cancers driven by oncogenic NOTCH signaling, based on the 69 articles included. Preclinical studies show that GSIs synergize with chemotherapy and radiotherapy, particularly in NSCLC, melanoma, and TNBC, and block EMT, overcome therapeutic resistance, and improve prognosis. Commonly used GSIs include DAPT and RO4929097, which enhance the efficacy of agents, such as gemcitabine (PDAC), paclitaxel, osimertinib, erlotinib, and crizotinib (NSCLC), and 5-FU (gastric cancer, TNBC). Promising strategies include combining GSIs with SAHA, ATRA, CB-103, and other NOTCH signaling targeting molecules, either alone or with chemo- and radiotherapy. Clinical trials with GSIs, however, remain limited. RO4929097 is the most extensively tested GSI in clinical settings. PDAC trials combining GSIs with gemcitabine showed no benefit; melanoma trials yielded modest outcomes; and TNBC trials demonstrated partial responses to GSIs but overall low efficacy and significant adverse events. Discussion and Conclusions. Despite encouraging preclinical evidence, clinical trials with GSIs have underperformed, largely due to tumor heterogeneity, dosing limitations, and the non-selective nature of γ-secretase inhibition. Other NOTCH inhibitors, such as DLL4 antibodies, also resulted in partial responses and secondary effects. Future strategies should prioritize receptor-specific NOTCH inhibitors, patient stratification based on NOTCH pathway activation, and optimized combination regimens. Emerging approaches include integrating immunotherapy with advanced technologies such as CRISPR, CAR-T cells, and bispecific antibodies, as well as targeted delivery systems to enhance efficacy and reduce toxicity. Additional research directions include addressing the tumor microenvironment and EMT-driven resistance, elucidating the mechanisms of immune evasion, and inhibiting tumor angiogenesis. Finally, leveraging artificial intelligence and big-data-driven personalized medicine, including sex-specific considerations, will be essential for improving patient outcomes.

## Linked entities

- **Genes:** NOTCH2 (notch receptor 2) [NCBI Gene 4853]
- **Proteins:** Notch (neurogenic locus notch homolog), nicD (N-formylmaleamate deformylase), Adam7 (ADAM metallopeptidase domain 7), DLL4 (delta like canonical Notch ligand 4)
- **Chemicals:** DAPT (PubChem CID 161272), RO4929097 (PubChem CID 49867930), gemcitabine (PubChem CID 60750), paclitaxel (PubChem CID 36314), osimertinib (PubChem CID 71496458), erlotinib (PubChem CID 176870), crizotinib (PubChem CID 11597571), 5-FU (PubChem CID 3385), SAHA (PubChem CID 5311), ATRA (PubChem CID 444795), CB-103 (PubChem CID 2735289)
- **Diseases:** metastatic melanoma (MONDO:0005191), gastric cancer (MONDO:0001056), NSCLC (MONDO:0005233)

## Full-text entities

- **Genes:** DLL4 (delta like canonical Notch ligand 4) [NCBI Gene 54567] {aka AOS6, delta4, hdelta2}
- **Diseases:** cancer (MESH:D009369), melanoma (MESH:D008545), carcinogenesis (MESH:D063646), PDAC (MESH:C537768), gastric cancer (MESH:D013274), toxicity (MESH:D064420)
- **Chemicals:** crizotinib (MESH:D000077547), RO4929097 (MESH:C545185), ATRA (MESH:D014212), erlotinib (MESH:D000069347), gemcitabine (MESH:D000093542), osimertinib (MESH:C000596361), paclitaxel (MESH:D017239), CB-103 (-), 5-FU (MESH:D005472), SAHA (MESH:D000077337)
- **Species:** Homo sapiens (human, species) [taxon 9606]

## Figures

7 figures with captions in the complete paper: https://tomesphere.com/paper/PMC12984106/full.md

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Source: https://tomesphere.com/paper/PMC12984106