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immune cell function to identify and target only external antigens while recognizing
self-produced antigens as non-threats (Shi et al. 2018). However, cancer cells
expressing immune checkpoints inhibitors like PD-1 and CTLA4 alter
co-stimulatory signals and elude or impede immune monitoring, resulting in tumor
growth and development. Therefore, efforts are focused on developing immunotherapeutic interventions to enhance antitumor immune response safely and effectively
(Blattman and Greenberg 2004).
PD-1 functions as an inhibitory signaling receptor on the surface of
T lymphocytes. Programmed cell death-ligand1 (PD-L1) is one of the ligands
which cancer cells commonly overexpress to inhibit function and stimulation of
lymphocytes, inhibiting T-cell-mediated eradication (Sharpe and Pauken 2018).
Recent research has revealed that checkpoint inhibition, which targets PD-1 or
PDL-1, is a successful therapy for several tumors, including melanoma, lymphoma,
lung cancer, head and neck cancer, and others that express high levels of PD-L-1 or
PD-1 overexpression in T cells (Chen et al. 2020). PD-L1 inhibitors are therefore
recognized as efficient, targeted therapies for preventing T-cell cancer evasion. An
anti-PD-1 antibody “pembrolizumab (Nivolumab)” binds with the PD-L1 on tumor
cells to stop it from interacting to the PD-1 on T cells and stopping T cell inhibition,
allowing T cells to kill cancer cells (Han et al. 2020). In a phase II KEYNOTE-180
clinical trial, EC patients who received pembrolizumab experienced overall remission rates of only 10%, with median overall survival times (mOS) of 5.8 months and
objective response rates (ORR) of 14.3% (Vivaldi et al. 2020). A similar study using
pembrolizumab observed ORR of 13.8% and 6.3% in EC patients with PD-L1
expression compared to PD-L1 negative patients, respectively (Shah et al. 2019).
Though the side effects of pembrolizumab including nausea, vomiting, and hypertension have not been thoroughly studied; however, these clinical studies result in
the FDA approval of pembrolizumab as a second-line therapy option for PD-L1
positive EC patients. Another anti-PD-L1 antibody Nivolumab has been approved
by the FDA as a secondary treatment for EC patients with advanced disease
(Barsouk et al. 2019).
A homolog of the CD28 protein, CTLA4 is a transmembrane protein that is only
expressed on activated T cells. It is a suppressor of IL-2 expres sion and an antagonistic regulator of T cells (preventing the entry into the G
phase of the cell cycle)
1
and thus allowing the cancer cells to escape the immune attack. CTLA4 has been
shown in certain studies to be an immune-based target for cancer treatment (Leach
et al. 1996). While many CTLA4-targeting antibodies, such as Ipilimumab and
Tremelimumab, are currently being used against various tumors, no clinical evidence of their effectiveness for EC patients is currently available (Zhao et al. 2018).
More recently, a fully humanized monoclonal antibody “Tremelimumab” has also
been investigated as a secondary therapy for metastatic melanoma (Comin-Anduix
et al. 2016). Another immunological checkpoint is the TIM-3 which significantly
inhibits CD4+ T helper cells and CD8+ cytotoxic T lymphocytes (Balajam et al.
2020). Recently Zhao et al. analyzed the expression of TIM-3 and PD-1 on CD8+
TILs in EC patient samples and observed that patients with high expression of PD-1
and high density of CD8+ TILs have worse relapse-free survival (RFS) and OS

226 I. R. Khan et al.
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(Zhao et al. 2020). Despite this, no drug is currently in use targeting TIM-3 in EC
patients (Alsina et al. 2018). Another crucial immune checkpoint protein, LAG-3, is
expressed by TILs, NK, and B cells. Similar to TIM3, no therapies targeting LAG-3
are currently ongoing in EC patients. While many vaccines effectively activate
cytotoxic T cells and target cancer-specific antigens, however such studies on EC
patients have shown mixed results attributed to the distinct molecular features of
EAC and ESCC subtypes (To et al. 2022). Therefore, future clinical studies should
be designed considering the potential variability among different tumors and their
subtypes. In addition, personalized cancer immunotherapy called adoptive T-cell
transfer uses the patient’s own autologous immune cells that have been altered and
amplified ex vivo. The use of adoptive T-cell therapy has increased survival in EC
(Gu et al. 2021). Despite these improvements, immunotherapy is associated with
immune-related adverse events (irAEs) such as cutaneous, gastrointestinal, endocrine, and liver toxicity. While many biomarkers can predict immunotherapy prognosis, the low efficacy of these biomarkers warrants new biomarker s predicting
immunotherapy response. An overview of therapeutic targets, clinical trials, and
key parameters in EC immunotherapy is shown in Table 1.
5 Conclusion and Future Directions
In the Western world, including the United States, EAC stands as the predominant
subtype of esophageal cancer EC. Despite remarkable advancements in multimodal
treatment modalities, the prognosis for EC patients remains disheartening, with the
average survival time falling short of a year. Consequently, there is an imperative
demand for innovative therapeutic approaches for advanced EAC and ESCC,
emphasizing targeted therapies that deliver exceptional efficacy and minimal adverse
effects.
The genesis of ESCC has been associated with genes such as p53 and retinoblastoma (Rb), wherein deleterious mutations render these tumor suppressor genes
ineffective, thereby fostering cancer development. The esophageal cancer TME
encompasses various immune cells, including NK cells, TAMs, T-regs, DCs,
MCs, MDSCs, neutrophils, TAPs, and a myriad of cytokines and chemokines that
play a vital role in cancer progression.
A multitude of clinical trials are currently underway to scrutinize the potential
benefits of conjoining cytotoxic and targeted therapies for EC patients. Concurrently,
researchers are delving into next-generation treatment strategies, encompassing peptide vaccines, adoptive T-cell therapy, oncolytic viruses, and the amalgamation of
immune-chemotherapy with radiation therapy. Nonetheless, given the low response
rates and the significant clinical and financial risks associated with immunotherapy, a
meticulous patient selection process is imperative to optimize treatment outcomes and
reduce unnecessary burden on patients.
In light of the pivotal role played by the TME in cancer development and
progression, it is of paramount importance to gain a comprehensive understanding
of the similarities and disparities among the TMEs in the various EC subtypes. This

Unraveling the Esophageal Cancer Tumor Microenvironment: Insights... 227
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Primary outcome
measures References
Patient
population
Clinical trial
identifier Phase Status
Reck et al. (2013)
NCT02743494 II Completed ESCC OS Kudo et al. (2017)
Curti et al. (2013)
tolerability
NCT02221960 I Completed ESCC, EAC Safety and
(2017)
tolerability
NCT02812875 I/II Completed ESCC, EAC ORR Papadopoulos et al.
Melisi et al. (2016)
tolerability
Vonderheide et al.
(2010)
tolerability
NCT02955251 I Completed ESCC, EAC Safety and
Rodriguez-Abreu et al.
(2020)
tolerability
No. Target Therapeutic strategy
Table 1 Overview of therapeutic targets, clinical trials, and key parameters in esophageal cancer immunotherapy
1 PD-1 Nivolumab
(pembrolizumab)
Ipilimumab NCT01938612 I/II Completed ESCC, EAC Safety and
4
2 PD-L1 Durvalumab NCT03040986 II Completed ESCC, EAC PFS Kelly et al. (2020)
3 CTLA-
4 IDO1 Indoximod NCT03301597 II EAC PFS Soliman et al. (2014)
antibody)
5 OX40 MEDI0562 (anti-OX40
6 VISTA CA-170 (VISTA
antagonist)
7 TGF-β Galunisertib NCT02581787 I Completed ESCC Safety and
antibody)
8 CD40 ABBV-428 (anti-CD40
9 LAG-3 Relatlimab NCT01968109 I/II Completed ESCC, EAC ORR Ascierto et al. (2017)
10 TIGIT Tiragolumab NCT03417037 I Completed ESCC, EAC Safety and

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invaluable insight will shed light on the heterogeneous signaling outcomes, patient
diversity, and differential responses to treatment, thereby paving the way for tailored
therapeutic strategies that cater to individual patient needs and enhance survival rates
in this devastating malignancy.
Ethics Approval and Consent to Participate Not applicable.
Consent for Publication All authors consent to publication.
Availability of Data Not applicable.
Competing Interests The authors declare no competing interests.
Funding This study was supported by the Ramalingaswami Fellowship (Grant number: DO NO.
BT/HRD/35/02/2006) from the Department of Biotechnology, & Core Research Grant
(CRG/2021/003805) from the Science and Engineering Research Board (SERB), Govt. of India,
New Delhi, Promotion of University Research and Scientific Excellence (PURSE) grant from the
Department of Biotechnology, Govt. of India, New Delhi, to the Islamic University of Science and
Technology (IUST), Awantipora to Dr. Macha, and Sidra Medicine Precision Program funding to
Ajaz A. Bhat (SDR400105).
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The Interplay Between Immunity and Gut
https://t.me/med1917
Microbiota in Colon Cancer
Lara Malaspina, Federica Petrelli, Bruno Perotti, Marco Arganini,
and Maria Raffaella Ambrosio
Abstract
Despite the introduction of valid screening programs and advances in therapies,
colorectal cancer (CRC) still remains one of the leading causes of death with an
increasing incidence in younger patients. The association of this tumor with
external modifiable factors such as life habits and diet is well known. In recent
years, growing attention has been focused on the intestinal microbiota, the
complex ecosystem made up of bacteria, viruses, and fungi, which plays a crucial
role in CRC tumorigenesis as well as in response to therapy. There are a lot of
mechanisms underlying the interplay between CRC and microbiota and their
identification is crucial to exploi t the microbiota in every phase, from prevention
to early identification of disease, as a new therapeuti c target and finally as a
biomarker of response to conventional therapy. In the following paragraphs, we
will elucidate the role of intestinal microbiota and immune system in CRC
carcinogenesis as well as their interplay. Moreover, we will address the potential
role of gut microbiota in CRC screening, diagnosis, and therapy.
Keywords
Carcinogenesis · Colon cancer · Dysbiosis · Gut microbiota
1 Introduction
CRC is one of the most common cancers ranking third in terms of incidence,
much higher in developed countries rathe r than in developing ones and accounting
for 1.9 million new cases in 2020 (Morgan et al. 2023). With its continued
L. Malaspina · F. Petrelli · B. Perotti · M. Arganini · M. R. Ambrosio (✉)
Azienda Sanitaria Toscana Nord Ovest, Pisa, Italy
e-mail: maradot@libero.it; mariaraffaella.ambrosio@uslnordovest.toscana.it
#
The Author(s), under exclusive license to Springer Nature Switzerland AG 2023
Interdisciplinary Cancer Research, https://doi.org/10.1007/16833_2023_179
Published online: 30 August 2023
233

234 L. Malaspina et al.
https://t.me/med1917
progression in Western countries, the incidence of CRC is predicted to increase to
2.2 million new cases and 1.1 million deaths in the next decade (Arnold et al. 2017).
The introduction of effective colonoscopy screening resulted in a shift to earlier
stage diagnosis (Siegel et al. 2022) and a subsequent decrease in mortality. If this is
true for people over 65 years, in the last decades, incidence increased in young adults
for whom the screening is not recommended. This trend, along with the continued
burden in the overall population, is alarming. Therefore, new screening strategies for
early detection and proper treatment are urgently needed (Song et al. 2020) along
with the implementation of known preventive measures.
Most CRCs are sporadic or non-inherited and well-known and modifiable environmental factors, such as diet and lifestyle (smoking, metabolic syndrome, consumption of red and processed meat; low consumption of fruits/vegetables, physical
inactivity, and heavy alcohol consumption) account for over 50% of sporadic CRC
(Song et al. 2020). Among them, the intestinal microbiota was recognized as an
important contributor and despite the long-standing association between CRC, diet,
and microbiome, which dates back to the 60 s (Aries et al. 1969), its role in CRC
initiation, progression, and metastasis was only recently investigated (Cheng et al.
2020; Drewes et al. 2016).
2 Gut Microbiota
Gut microbiota is a complex ecosystem derived from a proces s of host- microbes
coevolution that lasts for thousands of years and depends both on the host and on
their physiological environment (Sung et al. 2017).
Human gut microbiota is composed of an outstanding number (10
archaea, bacteria, eukaryotes, viruses, and microbes dominated by four main phyla:
Firmicutes, Bacteroidetes, Actinobacteria, and Proteobacteria (Gaines et al. 2018).
Their gene pool forms the so-called “microbiome” , exceeding the human genome by
150 times (Cheng et al. 2020). It is usually divided into two main groups: the “core
human microbiome” and the “variable human microbiome” the former comprises a
large proportion (38%) shared interindividually, the latter indicates microbial genes
belonging to a specific cohort of people. They are due to specific host characteristics
depending also on environmental changes and socio-cultural influences (Turnbaugh
et al. 2007) occurring after birth. Early, microorganisms colonize all the surfaces of
the human body exposed to external agents, reaching a stabilization within the first
year of life (Sung et al. 2017).
The lower tract of the gastrointestinal system harbors the greatest density and
diversity of microorganisms (Lee et al. 2021) and recent evidence revealed that these
communities and their collective genomes are not just passive bystanders but
actively maintain the physiology and health of the host by influencing basic
functions, such as metabolism, nutrition, tissue development, inflammation and
immunomodulation, and pathogen resistance regardless of health or disease status
(Ge et al. 2021), Mammals and their commensal microbes are normally symbiotic,
and the immune system has established various tolerance mechanisms. Specifically,
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to 1014)of
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