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EXPERIENTIAL LEARNING ON THE

APPLICATION OF MASS SPECTROMETRY
IN CANCER RESEARCH & DIAGNOSIS

INTRODUCTION

The human body is made up of trillions of cells that continuously grow, divide, and renew
themselves throughout our lives. Normally, when cells become damaged or old, they die off
and are cleared away. However, cancer begins when this natural process goes wrong—cells
start to grow uncontrollably and refuse to die, eventually overcrowding healthy cells and
disrupting the body's normal functions.

Cancer is one of the leading causes of death around the world. According to the American
Cancer Society, in 2024, it's estimated that every minute will see about 4 new cancer cases
and 1 death. To fight this growing threat, it’s crucial to understand the disease at a deeper,
biological level. Thanks to recent technological advancements, researchers now have access
to powerful tools that help in cancer diagnosis and study.

One such tool is Matrix-Assisted Laser Desorption/Ionization Time-of-Flight (MALDI-

TOF), a type of mass spectrometry. It allows scientists to analyze complex biological
samples—like tumor tissue or body fluids—with precision. This technique plays a key role in
early cancer detection by helping identify potential biomarkers that are vital for diagnosis and
treatment planning.

This report explores how MALDI-TOF works and highlights its valuable role in cancer
research, aiming to improve our understanding of cancer biology and advance more effective
treatment strategies.

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PROTEOMICS IN BIOMARKER DISCOVERY:

Proteomics is the large-scale study of proteins—their structures, functions, modifications, and

interactions—and has become one of the most powerful tools in modern biomedical research.
It offers deeper and more detailed insights than many traditional approaches, especially when
it comes to understanding diseases like cancer.

In cancer research, identifying reliable biomarkers is crucial. These biomarkers can significantly
improve early detection, help predict how the disease might progress, monitor treatment
effectiveness, and guide personalized therapy. Proteomics plays a key role by helping
scientists identify and analyze proteins that can act as diagnostic, prognostic, or predictive
markers.

One of the most effective tools in proteomics is mass spectrometry (MS). MS-based techniques
are widely used in laboratories to detect and measure proteins in various biological samples.
Typically, peptides are extracted from patient samples and analyzed using MS methods such
as LC-MS/MS or MALDI-TOF. These techniques generate spectra that show the mass-to-
charge (m/z) ratios of the peptides, which are then matched against protein databases.

By comparing the protein profiles of cancer patients to those of healthy individuals, researchers
can spot proteins that are expressed differently—these become strong candidates for cancer
biomarkers.

Fig: GENERAL STEPS IN PROTEOMICS – BASED BIOMARKER DISCOVERY

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Metabolomics and Lipidomics

Metabolomics
Metabolomics investigates metabolites as chemical substances generated by metabolic
processes while all cellular chemical transformations that provide cellular energy support
vital processes. The regulated sequence of small molecule reactions leads to metabolite
formation which supports organism health. Short-term variations in key metabolite
concentrations such as blood glucose responses to eating food affect health significantly
when observed independently of DNA and protein analysis. Metabolomics represents a
method to determine quantifiable traits of metabolic activity called molecular phenotypes.
Such data provides maximum utility when combined with genomic and proteomic and
transcriptomic data collection techniques for the study of an organism's genetic and molecular
profiles.
General Workflow

Application
- Precision medicine and disease diagnosis.
- Drug metabolism and pharmacokinetics.
- Nutritional and environmental research etc.

Lipidomics
Lipidomics is an emerging field that focuses on the comprehensive analysis of lipids in
biological systems. It helps understand lipid composition, structure, and function in health
and disease. It enables to know about lipid molecular species and their biological roles with
respect to expression of proteins involved in lipid metabolism and function including gene
regulation.It is a subgroup within the field called metabolomics.
General Workflow

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Applications:
- Biomarker discovery in cancer and neurodegenerative diseases.
- Understanding metabolic disorders (diabetes, obesity).
- Lipid-based drug development etc.

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DRUG DEVELOPMENT AND THERAPEUTIC MONITORING

Cancer is one of the major public health concerns worldwide, representing a major
life-threatening disease responsible for millions of deaths every year. Mass spectrometry (MS), has been
gaining increasing curiosity as it can help or monitor the disease to improve diagnosis and prognosis
through its high sensitivity and specificity. MALDI is the most widely used ionization method for
imaging cancer drug distribution in tumor and normal tissue samples with high spatial resolution and
acquisition speed.
Tandem mass spectrometry (MS/MS) or high-resolution mass spectrometry are often utilized in MALDI- MSI
for the identification of cancer drug molecules as well as their metabolic products.
MALDI-TOF MS has become a popular approach to establish potential cancer biomarkers, even at low
concentration levels. This analytical approach has an interesting potential as a clinical tool since it is easy
to use, cost-effective, and fast in terms of analysis time.
It consists of a soft ionization process by means of a laser that reaches the analyte mixed with a solution
of a matrix in an organic solvent [e.g. DHB] able to absorb energy in the form of UV light. The mixture is
first deposited onto a sample plate, in which the solvent then evaporates, and the sample is co-
crystallized. After a bombardment by a pulsed laser beam (UV or infrared radiation), the matrix
molecules that are energetically ablated from the surface of the sample transfer protons to the analyte,
resulting in the formation of intact gas-phase molecular ions (which usually carry a single positive
charge). After the ionization process, the masses can be analyzed by TOF MS (the heavier the ions, the
longer the time of
detection). The TOF reflector mode analyzer reflection mode provides a great resolution because it is
equipped with a longer flight path and electric fields that refocus ions by their masses.

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MALDI-TOF (Matrix assisted lase desorption/ionization- Time of Flight)

INTRODUCTION: The constituent particles are ionized and separated according to their mass-to- charge
ratio and measured through the time it will take them to reach the detector at the end of a
time-of-flight tube in MALDI-TOF MS analytical technique. In mass spectrometry, MALDI-TOF involves
the following:

• Mass ionization: matrix-assisted laser desorption/ionization (MALDI) and

• Mass analysis: time-of-flight (TOF) analysis.

It can be used for the analysis of a range of biological molecules, including peptides, proteins,
carbohydrate, oligonucleotide, etc. This is because ions that are formed have low internal energy.

WORKING PRINCIPLE: The MALDI TOF process is a two-phase procedure:

1.Ionization Phase
2. Time of Flight Phase

1. Ionization phase:
The samples are frozen into a crystalline matrix on a target plate and bombarded by a laser.
Thus, the molecules of the sample are evaporated into a certain vacuum and at the
same time are ionized. A high potential is then applied to accelerate the charged
particles.
2. Time-of-flight mass spectrometry phase:
I. In linear mode, the particles impact the linear detector within a few
nanoseconds after ionization; heavier molecules arrive later than lighter ones.
Flight time measurements
therefore allow for direct determination of the molecules' masses. Each peak in
the spectrum corresponds to a certain mass of the particle with respect to
the time axis beginning from the moment of ionization.
II. In reflector mode, particles deflect so that they fly toward the second detector. On
the one hand, the reflector extends the flight distance, but at the same time it
focuses on the
masses, and as a result of these two contributions, higher resolution than in linear mode
is achieved.

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MALDI IMAGING MASS SPECTROSCOPY

MALDI-IMS is a technique that allows for the direct acquisition of mass data for metabolites,
lipids, peptides, and proteins from tissue sections. It can be performed as a multiple spot
profiling or high resolution imaging experiment, providing molecular data that complements
histology and immuno-histochemistry, making it valuable for cancer biomarker research and
diagnostics.

MALDI-IMS analysis involves cutting tissues into thin sections and mounting them on
conductive slides. The slides are coated with a MALDI matrix, which depends on the
molecular size and chemical properties of the analyte. Imaging mass spectra are collected by
irradiating slides with a laser beam on the tissue area. The ion images are compared with
histologically stained tissue to investigate the analyte's distribution within specific
histological features.

Applications
Direct tissue section analysis using an MS instrument eliminates disruption and loss of spatial
proteome information. This method allows for molecular classification and grading, as tissue
sections can be prepared and analyzed quickly using standardized protocols.
Tissue-specific biomarkers can be visualized and identified using traditional proteomics methods
like LC-MS. MS measurement of molecules directly from tissue was first described in 1997.
Secondary ion MS (SIMS) or matrix-assisted laser desorption/ionisation (MALDI)
instruments are used to generate ions from tissue. MALDI requires a tissue section coated
with a low molecular weight organic molecule called the "matrix," which can be modified to
extract lipids, peptides, and proteins from the tissue.

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MALDI-TOF in High-Throughput Screening for Cancer Biomarkers :

Matrix-Assisted Laser Desorption/Ionization Time-of-Flight (MALDI-TOF) mass spectrometry
is a powerful tool for high-throughput screening in cancer biomarker discovery. It enables
rapid,
accurate, and sensitive detection of biomolecules such as proteins, peptides, and
metabolites in complex biological samples like serum, plasma, urine, or tissue.
In this technique, samples are mixed with a matrix that aids in ionization, then spotted onto
a MALDI plate. A laser pulse ionizes the molecules, which are analyzed based on their mass-
to-charge (m/z) ratio using TOF analyzers. The resulting spectral data provide molecular
fingerprints of the samples.
By comparing spectra from cancerous and healthy samples, researchers can identify distinct
molecular patterns—potential biomarkers.
MALDI-TOF is highly suitable for high-throughput workflows due to its minimal sample
preparation, fast analysis speed, and compatibility with automated systems. It allows
screening of thousands of samples in a short time, facilitating large-scale biomarker
discovery and validation.
Additionally, MALDI Imaging Mass Spectrometry (MALDI-IMS) adds spatial resolution,
allowing biomarker localization within tissue sections. Overall, MALDI-TOF accelerates the
discovery of
diagnostic, prognostic, and therapeutic biomarkers, playing a critical role in early cancer
detection and precision oncology.

MALDI-HTS Workflow Diagram

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TUMOUR MICROENVIRONMENT AND MICROBIAL ANALYSIS

The Tumour Microenvironment (TME) is now recognized as a critical driver in how cancer
progresses, how it resists treatment, and how it escapes the immune system. While once
thought to be just a mix of structural (stromal), blood vessel (vascular), and immune cells,
research now shows it also houses a rich microbial community — what scientists are
beginning to call the tumour
microbiome. These microbes, whether located directly in the tumour or in remote sites like the
gut, can shape the TME both directly and indirectly. Their impact reaches into inflammation,
metabolism, and even how the immune system fights back against tumours.
Understanding the interactions between microbes and the TME opens up exciting new paths
for diagnosis, prognosis, and targeted therapy.

Main components in the Tumour Microenvironment

 Cancer cells

 Cancer-associated fibroblasts (CAFs)

 Immune cells: T cells, tumour-associated macrophages (TAMs), dendritic cells, regulatory

T cells (Tregs)

 Endothelial cells and pericytes

 Extracellular matrix (ECM)

 Soluble signals: cytokines, chemokines, metabolites

 Resident or translocated microbes

How Microbes Influence the TME

Shape immune cell recruitment, blood vessel growth, and ECM re-
Microbial metabolites
modeling

Trigger immune receptors (like TLRs) on both immune and tumour cells
Bacterial antigens (PAMPs)

Chronic inflammation Creates an environment that supports tumour growth

Microbe–immune Affect T-cell activity, immune cell development, and immune checkpoint
interactions signaling

Impact on treatment Influence how well chemotherapy, radiation, or immunotherapy works

Example: Fusobacterium nucleatum in colorectal cancer helps tumours dodge the immune system and
resist chemo.

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Microbial Niches in Cancer

 Inside tumours: e.g., breast, pancreas, colon

 Mucosal surfaces: gut, mouth, cervix — common in mucosa-related cancers

 Gut microbiome: has systemic effects, especially on response to immunotherapy

Step-by-Step: Microbial Analysis in the Tumor

Microenvironment
A. Sample Collection

 Tumour samples (fresh or FFPE)

 Adjacent normal tissue

 Blood (for cfDNA, cytokines)

 Stool samples (for gut studies)

Note: Use sterile tools and DNA/RNA-free materials to avoid contamination.

B. Nucleic Acid Extraction

 Use DNA/RNA extraction kits tailored for microbial content

 Always include negative controls

C. Sequencing Techniques

1. 16S rRNA Sequencing – Basic bacterial ID at genus/species level

2. Metagenomic Shotgun Sequencing – Captures all DNA for detailed profiling

3. RNA-Sequencing/Dual RNA-Sequencing– Looks at both host and microbial gene expression

4. Single-Cell RNA-Sequencing + Microbial Detection – Finds bacteria inside individual

host cells

D. Data Analysis

 Quality control (e.g., Decontam)

 Taxonomy classification (QIIME2, Kraken2, MetaPhlAn)

 Functional insights (HUMAnN, KEGG, GO terms)

 Merge with host data:

Immune cell profiling (CIBERSORT, xCell)

Spatial mapping (e.g., 10X Visium with microbial tags)

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Pathway insights (GSEA, IPA)

E. Experimental Validation

 Confirm bacteria via qPCR or FISH

 Use IHC or IF for immune markers or ECM structure

 Measure cytokines with ELISA or multiplex

 Lab models: co-cultures, gnotobiotic (germ-free) mice

F. Link to Clinical Data

 Tumour type

 Patient survival

 Immunotherapy response

 Risk of recurrence or metastasis

Cutting-Edge Tools
 Spatial metagenomics – Pinpoints where bacteria live in tumour tissue

 Multi-omics platforms – Combine microbiome data with host gene activity, epigenetics,
and metabolism

 AI-based models – Predict how microbes influence therapy outcomes

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CLINICAL APPLICATION OF MALDI-TOF IN CANCER

o Understanding Tissue Structure Through Spatial Biology

MALDI imaging is often used in molecular histology to visualize the molecular makeup of tissues.
It helps researchers distinguish between different types of tissue—such as tumors and the
surrounding microenvironment—as well as between various tissue states like active tumor
regions and necrotic (dead) areas.
o Studying Tumor Heterogeneity
Even when tumors look uniform to the naked eye, their cells can have a wide range of genetic
differences. These differences may arise from cancer stem cells or clonal evolution. MALDI
imaging helps uncover this internal diversity by detecting peptides, proteins, N-glycans, or
metabolites in specific regions of a tumor.
o Assessing Surgical Resection Margins
For cancers like sarcomas, surgery is often the primary treatment. However, it's difficult to
distinguish tumor tissue from healthy tissue during surgery. Afterward, a pathologist examines
the tissue edges (resection margins) to confirm complete tumor removal. MALDI imaging can
enhance accuracy in determining whether enough non-cancerous tissue was removed, which is
critical to prevent recurrence and reduce the need for additional therapy.
o Finding Diagnostic Biomarkers
MALDI imaging has proven helpful in identifying biomarkers for diagnosing sarcomas. It can help
differentiate between sarcoma types and grades, enabling quicker classification of new tumor
samples. This approach could even reveal new molecular subtypes that influence clinical decision-
making.
o Identifying Prognostic Biomarkers
Using MALDI imaging to study proteins, metabolites, and N-glycans has led to the discovery of
biomarkers linked to patient outcomes. The technique’s ability to provide spatial data allows for
the identification of biomarkers specific to certain sarcoma types—some of which would be
missed using bulk tissue analysis. It can also reveal common markers across multiple high-grade
sarcoma subtypes, making it easier to assess disease severity in complex cases.
o Analyzing Drug Response and Toxicity
MALDI imaging is well-suited to measure how tumors respond to drugs, especially in a spatially
precise way. It can detect both the drug’s distribution and changes in the tissue, such as
resistance mechanisms. This is especially valuable in sarcomas, which often develop resistance to
treatment.
o Visualizing Drug Distribution
In cancer research, MALDI imaging has become a go-to method for studying how drugs spread
through tissue, how effective they are, and whether they cause side effects. Unlike traditional
imaging methods, MALDI doesn’t require any labeling, which makes the process simpler, faster,
and less expensive. It also allows researchers to study drugs alongside other molecules like lipids
and metabolites all at once, offering a complete picture of the drug’s impact.

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FUTURE PERSPECTIVE

MALDI-TOF Mass Spectrometry (MS) holds great promise for transforming cancer diagnostics by
enabling the discovery of biomarkers, visualizing tissues at the molecular level, and quantifying key
biological markers. However, its use as a routine diagnostic tool in cancer care is still developing. For it
to reach its full potential, several important factors need to be addressed—such as improving validation
processes, standardizing methods, refining data interpretation, enhancing sensitivity and specificity,
managing costs, and broadening the range of detectable biomarkers.

To ensure consistent and reliable results, it is essential to standardize steps like sample preparation,
instrument calibration, and data analysis. Beyond identifying a single target, MALDI-TOF MS also
allows for mass fingerprinting, offering a more comprehensive look at molecular profiles.

 Predicting Therapy Response

MALDI imaging can help identify predictive biomarkers—molecules that can forecast how well a patient
will respond to a specific therapy. This would allow doctors to tailor treatment plans, making them more
effective while reducing side effects. While current treatment strategies for sarcomas are highly
individualized, they often lack universal predictive markers. MALDI imaging, with its speed, affordability,
and ability to scan multiple molecules at once, could become a valuable tool for patient stratification in
future cancer care.
 Multimodal and Multi-Omics Integration

To gain deeper insights from a single tissue sample, MALDI imaging can be combined with other imaging
and "omics" techniques (like genomics and transcriptomics). Since the tissue remains intact after MALDI
analysis, it can easily be re-used for other spatial or molecular studies—especially useful in exploring rare
cancers with complex molecular signatures.
 Evaluating Preclinical Cancer Models

For rare cancers like sarcomas, suitable lab models are often limited or nonexistent. MALDI imaging can
help fill this gap by analyzing and comparing the molecular structure of these models to actual human
tumor tissues. This makes it easier to validate or develop new models, supporting research into disease
behavior and treatment responses.

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Conclusion:
MALDI-TOF mass spectrometric technology has opened up new avenues for
high-sensitivity analysis of complex biological specimens and cancer research
or diagnosis. In the case of MALDI-TOF, it consists of a two-phase process:
ionization (sample bombardment by laser) and time-of-flight analysis (mass
determination via flight time to detector). As a result, it now is possible to
analyze biomolecules quickly and without much preparation, making this
system invaluable for discovering cancer biomarkers.
From the proteomics, also helped through MALDI-TOF, is that it could enable
characterization of potential diagnostic, prognostic, and predictive cancer
biomarkers by comparing mass-to-charge ratio spectra between cancer patients
and healthy individuals. In fact, high-throughput capabilities allow this process
so that thousands of samples can be very quickly screened for the initial large-
scale biomarker discovery-validation effort.
A great stride has been made with MALDI Imaging Mass Spectrometry, which
allows for the extraction of molecular data from tissue sections while still
preserving spatial information. This adds another layer to histology since
molecular data are now correlated with tissue characteristics without disrupting
spatial proteome information and helps build pictures of heterogeneity in the
tumor microenvironment. The applications of MALDI-IMS further extend into
metabolomics and lipidomics, providing a peek into altered metabolic pathways
during cancer progression.

Drug development utilizes MALDI more widely than any other method for
imaging cancer drug distribution in tissues with subcellular resolution,
facilitating identification of drug molecules and their metabolic products
without any labeling necessity.

In the clinic:
1. Molecular histology study for spatial biological comparison
2. Intratumor heterogeneity study
3. Evaluation of surgical resection margins, particularly in sarcomas
4. Diagnostic and prognostic biomarkers identification

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5. Drug response, resistance, and toxicity studies

6. Label-free drug distribution imaging.

Future Directions:
1. Predictive biomarker identification for therapy stratification
2. Multidimensional, multi-omics imaging from a single section to extract
maximal information
3. Validation of preclinical models using molecular histology against human
tissues
Standardization of protocols, validation, sensitivity, cost, and increased biomarker
coverage are challenges faced by the technique before it can reach its full
clinical potential.
An emerging area of research and investigation now encompasses the study of
interplay between the tumor microenvironment (TME) and its associated
microbial community. Tumor-associated microbiomes act through microbial
metabolites, trigger bacterial antigens to induce immune receptors, chronic
inflammation, interfere with microbe-immune interactions that ultimately result
in altered T cell activity and efficacy of treatment. This requires sterile sample
collection for nucleic acid extraction using specialized protocols, various
sequencing techniques, sophisticated data analysis, validation, and clinically
relevant correlation. There is an emerging tool to understand the co-operating
microbe in cancer progression and treatment outcome, including spatial
metagenomics, multi-omics platforms, and AI-based models.
MALDI-TOF mass spectrometry thus paves the way for the analysis of complex
biological samples with high sensitivity and specificity, imaging capabilities,
and high-throughput screening for biomarker discovery, drug development, and
clinical diagnosis. It promises an increasingly greater role for MALDI-TOF in
precision oncology as improvements in standardization and technology allow
for increasingly earlier detection, more accurate prognosis, and more effective
personalized treatment.

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therapy oncolytics, 21, 255–263. https://doi.org/10.1016/j.omto.2021.04.006
 Newgard, Chris, Bain, James. "metabolomics". Encyclopedia Britannica, 27 Apr. 2024,
https://www.britannica.com/science/metabolomics. Accessed 5 April 2025
 https://microbeonline.com/maldi-tof-ms-principle-applications-microbiology/
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MALDI Imaging Mass Spectrometry (MALDI-IMS)-application of
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 Cazares, L. H., Troyer, D. A., Wang, B., Drake, R. R., & Semmes, O. J. (2011). MALDI tissue imaging:
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