Next Article in Journal
Current Landscape of Immune Checkpoint Inhibitors for Metastatic Urothelial Carcinoma: Is There a Role for Additional T-Cell Blockade?
Previous Article in Journal
Disparities in Breast Cancer Diagnostics: How Radiologists Can Level the Inequalities
Previous Article in Special Issue
Prognostic Significance of Integrin Subunit Alpha 2 (ITGA2) and Role of Mechanical Cues in Resistance to Gemcitabine in Pancreatic Ductal Adenocarcinoma (PDAC)
 
 
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Editorial

Revolutionizing Cancer Treatment: Unveiling New Frontiers by Targeting the (Un)Usual Suspects

1
Institute of Genetics and Biophysics (IGB), National Research Council of Italy (CNR), 80131 Naples, Italy
2
Department of Medical Oncology, Amsterdam UMC, VU University, Cancer Center Amsterdam, 1081 HV Amsterdam, The Netherlands
3
Fondazione Pisana per la Scienza, San Giuliano Terme, 56124 Pisa, Italy
*
Author to whom correspondence should be addressed.
These authors contributed equally to this work.
Cancers 2024, 16(1), 132; https://doi.org/10.3390/cancers16010132
Submission received: 28 November 2023 / Accepted: 15 December 2023 / Published: 27 December 2023
(This article belongs to the Special Issue Targeting the (Un)Usual Suspects in Cancer)
This Special Issue includes original articles and reviews on both established and innovative approaches to cancer targeting, showcased at the 29th IGB Workshop titled “Targeting the (un)usual suspects in cancer” “https://29thigbworkshop.sciforum.net/ (accessed on 19 December 2023), held on 2–3 December 2021.
Since the inception of the “war on cancer” 52 years ago through the US National Cancer Act, numerous therapeutic strategies promoting the death of cancer cells have been developed, resulting in a diverse range of available cancer treatments [1,2]. However, conventional treatments often lack selectivity in killing tumor cells, facing challenges due to the tumor heterogeneity [3,4]. In this context, the identification of new drugs or drug combinations targeting well-known signaling pathways [5,6], along with the repurposing of approved drugs with undiscovered antitumor activities [7,8,9], offer refreshed arrays of therapeutic options in oncology. Among them, anastrozole, an aromatase inhibitor, demonstrated new antitumor activities in breast cancer [10].
Federico et al. introduced an innovative network pharmacology strategy, combining mechanistic and chemocentric approaches to drug repositioning [11]. This involves a multilayer network-based computational framework integrating disease perturbational signatures with drug intrinsic characteristics, encompassing factors such as their mechanism of action and chemical structure. Public data from The Cancer Genome Atlas were used [https://www.cancer.gov/tcga (accessed on 27 November 2023)], identifying paclitaxel as a promising candidate for combination therapy across various cancer types [11]. Furthermore, in the spirit of drug repositioning, the analysis identified several non-cancer-related unconventional drug targets as potential candidates for combinatorial pharmacological intervention in cancer treatment. These include hormonal drugs (carbimazole and methimazole), psychoanaleptics (phenelzine, tranylcypromine, and pentobarbital), calcium channel blockers (perhexiline), and antihypertensives (clonidine). These promising findings support the use of this framework as a tool to facilitate the prioritization of drug combinations and repositioning by integrating the mechanistic characteristics of the disease with the intrinsic properties of the drugs.
A different approach was described by Casalino et al., who reviewed diverse strategies aiming to inhibit tumor growth, metastasis, and drug resistance by targeting the FOS-family transcription factor Fra-1, encoded by FOSL1 gene, which has emerged as a notable therapeutic target within the AP-1 complex [12]. Fra-1 is frequently overexpressed in various solid tumors, triggered by major oncogenic pathways like BRAF-MAPK, Wnt-beta-catenin, Hippo-YAP, and IL-6-Stat3. In agreement with new approaches targeting transcription factors in cancer [13], the discussed strategies include the design—and tumor-specific delivery—of Fra-1/AP-1-specific drugs, RNA-based therapeutics targeting the FOSL1 gene, its mRNA, or regulatory circular RNAs (circRNAs), blocking peptides, small-molecule inhibitors, and innovative Fra-1 protein degraders.
A novel therapeutic strategy was also described in the study by Che et al. [14], using a previously established array of pancreatic ductal adenocarcinoma (PDAC) cell lines, primary cultures, and chorioallantoic membrane models [15]. This strategy involved the utilization of nanotechnology for the delivery of chemotherapeutics, with a preference for radiosensitizing agents, aiming to enhance the efficacy of chemoradiation. The study specifically assessed the impact of biodegradable ultrasmall-in-nano architectures (NAs) containing gold ultra-small nanoparticles enclosed in silica shells loaded with a cisplatin prodrug (NAs-cisPt) in combination with ionizing radiation (IR). The main findings highlighted the heightened cytotoxic effect of NAs-cisPt, particularly through the controlled release of the cisplatin prodrug [14]. Given cisplatin’s recognized role as a radiosensitizer [16], the administration of the cisplatin prodrug in a controlled manner through encapsulation presents a promising and innovative treatment approach. Moreover, a recent study showed that PDAC paclitaxel-resistant cells exhibit enhanced sensitivity to IR due to the greater accumulation of DNA damage depending on the radiation-induced modulation of autophagy and of the Hippo pathway [17], prompting further research on new strategies to promote the antitumor effects of IR in PDAC [18].
Apart from key genetic factors, desmoplasia and the tumor microenvironment (TME) have been recognized as key contributors to PDAC chemoresistance [19,20], and Gregori et al. integrated biomechanical and pharmacological approaches to investigate the role of the cell-adhesion molecule Integrin Subunit Alpha 2 (ITGA2), a crucial regulator of the extracellular matrix [21], in PDAC resistance to gemcitabine [22]. Notably, high ITGA2 expression was correlated with shorter progression-free and overall survival, indicating its prognostic significance and association with gemcitabine treatment ineffectiveness. Transcriptomic and proteomic analyses revealed upregulated ITGA2 in gemcitabine-resistant cells, whereas silencing ITGA2 reduced the aggressive behavior of these cells both in vitro and in vivo, associated with the upregulation of phospho-AKT.
Notably, the PI3K/AKT/mTOR signaling pathway, a crucial downstream effector of KRAS, plays a significant role in regulating key hallmarks of cancer [23], and several studies support the application of agents targeting the PI3K/AKT/mTOR pathway in the context of PDAC [24,25,26]. However, for certain tumors, such as colorectal and PDAC, even highly selective therapies fail to completely eradicate the disease because they do not target the niche of cancer stem cells (CSCs), capable of reconstituting and perpetuating malignancy [27]. Therefore, targeting pathways specific to the maintenance of CSCs and disrupting communication between tumor cells and the TME are emerging as additional fundamental approaches in the ongoing “war on cancer” [28,29].
For instance, a recent study reported a LAMC2-expressing cell population, which is endowed with enhanced self-renewal capacity and is sufficient for tumor initiation and differentiation and driving metastasis [30]. The profiling of these cells indicated a prominent squamous signature and differentially activated pathways critical for tumor growth and metastasis, including the deregulation of the TGF-β signaling pathway [30], a key pathway in the biology of cancer progression [31]. Treatment with Vactosertib, a new small-molecule inhibitor of the TGF-β type I receptor, completely abrogated lung metastasis, primarily originating from LAMC2-expressing cells [30].
Lastly, the list of tumor hallmarks and cancer-causing factors has been updated in the last decade to include new cellular processes (e.g., metabolism; [32,33]) and molecular factors (e.g., non-coding RNAs; [34]) as significant contributors to tumor onset, progression, and drug sensitivity. Despite metabolic alterations being reported approximately a century ago [35], targeting tumor metabolism has recently regained interest as a plausible interventional strategy [36,37]. Additionally, mounting evidence suggests a previously unrecognized role for long non-coding RNAs (lncRNAs) as oncogenes and tumor suppressors due to their ability to regulate various cancer hallmarks. These findings, particularly the cancer-specific expression of most lncRNAs, establish the rationale for considering lncRNAs as therapeutic targets [38,39], as silencing them would not induce side effects in other tissues or cell types.
In summary, echoing the famous sentence expressed in the renowned crime movie The Usual Suspects, which states, “The greatest trick the devil ever pulled was convincing the world he didn’t exist”, it becomes apparent that concentrating solely on recognized oncogenic factors can narrow our perspectives and limit the effectiveness of existing cancer therapies [40]. This underscores the need to delve into novel therapeutic targets and approaches, encompassing new strategies that involve the individual—or in some cases simultaneous—targeting of the TME, metabolism, CSCs, and non-coding RNAs.

Funding

This work is supported by: IG AIRC Grant (#24444) to E.G., My First AIRC Grant (MFAG #23453) to V.C., Bridge AIRC Grant (#27012) to E.L.

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. Heng, J.; Heng, H.H. Genome Chaos, Information Creation, and Cancer Emergence: Searching for New Frameworks on the 50th Anniversary of the “War on Cancer”. Genes 2021, 13, 101. [Google Scholar] [CrossRef]
  2. Ramalingam, S.S.; Khuri, F.R. The National Cancer Act of 1971: A seminal milestone in the fight against cancer. Cancer 2021, 127, 4532–4533. [Google Scholar] [CrossRef]
  3. Allen, G.M.; Lim, W.A. Rethinking cancer targeting strategies in the era of smart cell therapeutics. Nat. Rev. Cancer 2022, 22, 693–702. [Google Scholar] [CrossRef]
  4. Ben-David, U.; Beroukhim, R.; Golub, T.R. Genomic evolution of cancer models: Perils and opportunities. Nat. Rev. Cancer 2019, 19, 97–109. [Google Scholar] [CrossRef]
  5. Caunt, C.J.; Sale, M.J.; Smith, P.D.; Cook, S.J. MEK1 and MEK2 inhibitors and cancer therapy: The long and winding road. Nat. Rev. Cancer 2015, 15, 577–592. [Google Scholar] [CrossRef]
  6. Kanev, G.K.; Zhang, Y.; Kooistra, A.J.; Bender, A.; Leurs, R.; Bailey, D.; Würdinger, T.; de Graaf, C.; de Esch, I.J.P.; Westerman, B.A. Predicting the target landscape of kinase inhibitors using 3D convolutional neural networks. PLoS Comput. Biol. 2023, 19, e1011301. [Google Scholar] [CrossRef]
  7. Wieder, R.; Adam, N. Drug repositioning for cancer in the era of AI, big omics, and real-world data. Crit. Rev. Oncol. Hematol. 2022, 175, 103730. [Google Scholar] [CrossRef]
  8. Brummer, C.; Faerber, S.; Bruss, C.; Blank, C.; Lacroix, R.; Haferkamp, S.; Herr, W.; Kreutz, M.; Renner, K. Metabolic targeting synergizes with MAPK inhibition and delays drug resistance in melanoma. Cancer Lett. 2019, 442, 453–463. [Google Scholar] [CrossRef]
  9. Aprile, M.; Cataldi, S.; Perfetto, C.; Federico, A.; Ciccodicola, A.; Costa, V. Targeting metabolism by B-raf inhibitors and diclofenac restrains the viability of BRAF-mutated thyroid carcinomas with Hif-1α-mediated glycolytic phenotype. Br. J. Cancer 2023, 129, 249–265. [Google Scholar] [CrossRef]
  10. Mahase, E. Anastrozole: Repurposed drug could prevent thousands of breast cancer cases. BMJ 2023, 383, 2608. [Google Scholar] [CrossRef]
  11. Federico, A.; Fratello, M.; Scala, G.; Möbus, L.; Pavel, A.; Del Giudice, G.; Ceccarelli, M.; Costa, V.; Ciccodicola, A.; Fortino, V.; et al. Integrated Network Pharmacology Approach for Drug Combination Discovery: A Multi-Cancer Case Study. Cancers 2022, 14, 2043. [Google Scholar] [CrossRef] [PubMed]
  12. Casalino, L.; Talotta, F.; Cimmino, A.; Verde, P. The Fra-1/AP-1 Oncoprotein: From the “Undruggable” Transcription Factor to Therapeutic Targeting. Cancers 2022, 14, 1480. [Google Scholar] [CrossRef] [PubMed]
  13. Bushweller, J.H. Targeting transcription factors in cancer—From undruggable to reality. Nat. Rev. Cancer 2019, 19, 611–624. [Google Scholar] [CrossRef] [PubMed]
  14. Che, P.P.; Mapanao, A.K.; Gregori, A.; Ermini, M.L.; Zamborlin, A.; Capula, M.; Ngadimin, D.; Slotman, B.J.; Voliani, V.; Sminia, P.; et al. Biodegradable Ultrasmall-in-Nano Architectures Loaded with Cisplatin Prodrug in Combination with Ionizing Radiation Induces DNA Damage and Apoptosis in Pancreatic Ductal Adenocarcinoma. Cancers 2022, 14, 3034. [Google Scholar] [CrossRef] [PubMed]
  15. Nowak-Sliwinska, P.; van Beijnum, J.R.; van Berkel, M.; van den Bergh, H.; Griffioen, A.W. Vascular regrowth following photodynamic therapy in the chicken embryo chorioallantoic membrane. Angiogenesis 2010, 13, 281–292. [Google Scholar] [CrossRef] [PubMed]
  16. Tan, W.J.T.; Vlajkovic, S.M. Molecular Characteristics of Cisplatin-Induced Ototoxicity and Therapeutic Interventions. Int. J. Mol. Sci. 2023, 24, 16545. [Google Scholar] [CrossRef] [PubMed]
  17. Che, P.P.; Gregori, A.; Bergonzini, C.; Ali, M.; Mantini, G.; Schmidt, T.; Finamore, F.; Rodrigues, S.M.F.; Frampton, A.E.; McDonnell, L.A.; et al. Differential sensitivity to ionizing radiation in gemcitabine- and paclitaxel-resistant pancreatic cancer cells. Int. J. Radiat. Oncol. Biol. Phys. 2023. online ahead of print. [Google Scholar] [CrossRef] [PubMed]
  18. Waissi, W.; Paix, A.; Nicol, A.; Noël, G.; Burckel, H. Targeting DNA repair in combination with radiotherapy in pancreatic cancer: A systematic review of preclinical studies. Crit. Rev. Oncol. Hematol. 2020, 153, 103060. [Google Scholar] [CrossRef]
  19. Gu, Y.; Chen, Q.; Yin, H.; Zeng, M.; Gao, S.; Wang, X. Cancer-associated Fibroblasts in Neoadjuvant Setting for Solid Cancers. Crit. Rev. Oncol. Hematol. 2023, 4, 104226. [Google Scholar] [CrossRef]
  20. Hingorani, S.R. Epithelial and stromal co-evolution and complicity in pancreatic cancer. Nat. Rev. Cancer 2023, 23, 57–77. [Google Scholar] [CrossRef]
  21. Bergonzini, C.; Kroese, K.; Zweemer, A.J.M.; Danen, E.H.J. Targeting Integrins for Cancer Therapy—Disappointments and Opportunities. Front. Cell Dev. Biol. 2022, 10, 863850. [Google Scholar] [CrossRef] [PubMed]
  22. Gregori, A.; Bergonzini, C.; Capula, M.; Mantini, G.; Khojasteh-Leylakoohi, F.; Comandatore, A.; Khalili-Tanha, G.; Khooei, A.; Morelli, L.; Avan, A.; et al. Prognostic Significance of Integrin Subunit Alpha 2 (ITGA2) and Role of Mechanical Cues in Resistance to Gemcitabine in Pancreatic Ductal Adenocarcinoma (PDAC). Cancers 2023, 15, 628. [Google Scholar] [CrossRef] [PubMed]
  23. Hussain, N.; Das, D.; Pramanik, A.; Pandey, M.K.; Joshi, V.; Pramanik, K.C. Targeting the complement system in pancreatic cancer drug resistance: A novel therapeutic approach. Cancer Drug. Resist. 2022, 5, 317–327. [Google Scholar] [CrossRef] [PubMed]
  24. Xu, R.; Song, J.; Ruze, R.; Chen, Y.; Yin, X.; Wang, C.; Zhao, Y. SQLE promotes pancreatic cancer growth by attenuating ER stress and activating lipid rafts-regulated Src/PI3K/Akt signaling pathway. Cell Death Dis. 2023, 14, 497. [Google Scholar] [CrossRef] [PubMed]
  25. Khan, S.; Budamagunta, V.; Zhou, D. Targeting KRAS in pancreatic cancer: Emerging therapeutic strategies. Adv. Cancer Res. 2023, 159, 145–184. [Google Scholar] [PubMed]
  26. Ingle, K.; LaComb, J.F.; Graves, L.M.; Baines, A.T.; Bialkowska, A.B. AUM302, a novel triple kinase PIM/PI3K/mTOR inhibitor, is a potent in vitro pancreatic cancer growth inhibitor. PLoS ONE 2023, 18, e0294065. [Google Scholar] [CrossRef] [PubMed]
  27. Mai, Y.; Su, J.; Yang, C.; Xia, C.; Fu, L. The strategies to cure cancer patients by eradicating cancer stem-like cells. Mol. Cancer 2023, 22, 171. [Google Scholar] [CrossRef] [PubMed]
  28. Bayik, D.; Lathia, J.D. Cancer stem cell-immune cell crosstalk in tumour progression. Nat. Rev. Cancer 2021, 21, 526–536. [Google Scholar] [CrossRef]
  29. Phan, T.G.; Croucher, P.I. The dormant cancer cell life cycle. Nat. Rev. Cancer 2020, 20, 398–411. [Google Scholar] [CrossRef]
  30. Cave, D.D.; Buonaiuto, S.; Sainz, B.; Fantuz, M., Jr.; Mangini, M.; Carrer, A.; Di Domenico, A.; Iavazzo, T.T.; Andolfi, G.; Cortina, C.; et al. LAMC2 marks a tumor-initiating cell population with an aggressive signature in pancreatic cancer. J. Exp. Clin. Cancer Res. 2022, 41, 315. [Google Scholar] [CrossRef]
  31. Derynck, R.; Turley, S.J.; Akhurst, R.J. TGFβ biology in cancer progression and immunotherapy. Nat. Rev. Clin. Oncol. 2021, 18, 9–34. [Google Scholar] [CrossRef] [PubMed]
  32. Hanahan, D.; Weinberg, R.A. Hallmarks of cancer: The next generation. Cell 2011, 144, 646–674. [Google Scholar] [CrossRef] [PubMed]
  33. Pavlova, N.N.; Thompson, C.B. The emerging hallmarks of cancer metabolism. Cell Metab. 2016, 23, 27–47. [Google Scholar] [CrossRef] [PubMed]
  34. Gutschner, T.; Diederichs, S. The hallmarks of cancer: A long non-coding RNA point of view. RNA Biol. 2012, 9, 703–719. [Google Scholar] [CrossRef] [PubMed]
  35. Warburg, O.; Wind, F.; Negelein, E. The metabolism of tumors in the body. J. Gen. Physiol. 1927, 8, 519–530. [Google Scholar] [CrossRef]
  36. Kroemer, G.; Pouyssegur, J. Tumor cell metabolism: Cancer’s Achilles’ heel. Cancer Cell 2008, 13, 472–482. [Google Scholar] [CrossRef]
  37. Fendt, S.M.; Frezza, C.; Erez, A. Targeting Metabolic Plasticity and Flexibility Dynamics for Cancer Therapy. Cancer Discov. 2020, 10, 1797–1807. [Google Scholar] [CrossRef]
  38. Zhu, S.; Li, W.; Liu, J.; Chen, C.H.; Liao, Q.; Xu, P.; Xu, H.; Xiao, T.; Cao, Z.; Peng, J.; et al. Genome-scale deletion screening of human long non-coding RNAs using a paired-guide RNA CRISPR-Cas9 library. Nat. Biotechnol. 2016, 34, 1279–1286. [Google Scholar] [CrossRef]
  39. Arun, G.; Diermeier, S.D.; Spector, D.L. Therapeutic Targeting of Long Non-Coding RNAs in Cancer. Trends Mol. Med. 2018, 24, 257–277. [Google Scholar] [CrossRef]
  40. Brock, A.; Huang, S. Precision Oncology: Between Vaguely Right and Precisely Wrong. Cancer Res. 2017, 77, 6473–6479. [Google Scholar] [CrossRef]
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

Share and Cite

MDPI and ACS Style

Costa, V.; Giovannetti, E.; Lonardo, E. Revolutionizing Cancer Treatment: Unveiling New Frontiers by Targeting the (Un)Usual Suspects. Cancers 2024, 16, 132. https://doi.org/10.3390/cancers16010132

AMA Style

Costa V, Giovannetti E, Lonardo E. Revolutionizing Cancer Treatment: Unveiling New Frontiers by Targeting the (Un)Usual Suspects. Cancers. 2024; 16(1):132. https://doi.org/10.3390/cancers16010132

Chicago/Turabian Style

Costa, Valerio, Elisa Giovannetti, and Enza Lonardo. 2024. "Revolutionizing Cancer Treatment: Unveiling New Frontiers by Targeting the (Un)Usual Suspects" Cancers 16, no. 1: 132. https://doi.org/10.3390/cancers16010132

APA Style

Costa, V., Giovannetti, E., & Lonardo, E. (2024). Revolutionizing Cancer Treatment: Unveiling New Frontiers by Targeting the (Un)Usual Suspects. Cancers, 16(1), 132. https://doi.org/10.3390/cancers16010132

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop